CN108446276B - Method and device for determining keywords of song list - Google Patents
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Abstract
The disclosure relates to a method and a device for determining song list keywords, and belongs to the technical field of software. The method comprises the following steps: determining at least one attribute descriptor corresponding to each song according to at least one item of song attribute information of each song; determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the attribute item to which at least one attribute descriptor corresponding to each song belongs and the preset sequence of different attribute items; determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors; selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors; and determining the selected attribute descriptors as the song menu keywords of the target song menu. By adopting the method and the device, the keyword is selected through the algorithm, and the efficiency is higher than that of a mode of manually inputting the keyword by thinking the keyword.
Description
Technical Field
The present disclosure relates to the field of software technologies, and in particular, to a method and an apparatus for determining keywords of a song menu.
Background
Some users who like music can build a song list according to the preference of the users, and the song list can comprise some songs which are enjoyed by the users. After the song list is established, the user can share the song list to other users through the operation terminal.
In the process, the method can simply and clearly lead other users to know the characteristics of the shared song list, such as the song style, the rhythm, the melody and the like by adding one or more song list keywords to the song list.
The user often manually inputs keywords for the menu based on the knowledge of the user on the song, and the efficiency of adding keywords for the menu is low.
Disclosure of Invention
In order to overcome the problems in the related art, the present disclosure provides the following technical solutions:
according to a first aspect of embodiments of the present disclosure, there is provided a method of determining a song list keyword, the method including:
acquiring at least one item of song attribute information of each song included in a target song list;
determining at least one attribute descriptor corresponding to each song according to the at least one item of song attribute information of each song;
sorting the at least one item of song attribute information according to a preset sequence, wherein the preset sequence is a paragraph structure;
determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the attribute item to which at least one attribute descriptor corresponding to each song belongs and the preset sequence of different attribute items;
determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors;
selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors;
and determining the selected attribute descriptors as the song menu keywords of the target song menu.
Optionally, the method further comprises:
acquiring at least one item of attribute information of the target song list;
determining at least one attribute descriptor corresponding to the target song list according to the attribute information of the song list;
determining the link-in relation and the link-out relation of each attribute descriptor and other attribute descriptors based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the preset ordering of different attribute items, including:
and determining the in-linking relation and the out-linking relation between each attribute descriptor and other attribute descriptors based on the sequence of the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the attribute item to which the at least one attribute descriptor corresponding to the target song list belongs and preset different attribute items.
Optionally, the determining at least one attribute descriptor corresponding to each song according to the at least one item of song attribute information of each song includes:
determining the attribute information in the word form as attribute descriptors corresponding to the songs for the attribute information in the word form in the at least one item of song attribute information of each song;
and for the sentence-form attribute information in at least one item of song attribute information of each song, performing word segmentation on the sentence-form attribute information, and determining words obtained by word segmentation as attribute descriptors corresponding to the songs.
Optionally, the determining the criticality corresponding to each attribute descriptor according to the determined in-link relation and out-link relation between each attribute descriptor and other attribute descriptors includes:
determining the corresponding criticality of each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
Optionally, the determining the link-in relationship and the link-out relationship between each attribute descriptor and other attribute descriptors based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the preset ordering of different attribute items includes:
and determining that at least one attribute descriptor and other attribute descriptors sequenced before the at least one attribute descriptor have a link-in relation and determining that at least one attribute descriptor and other attribute descriptors sequenced after the at least one attribute descriptor have a link-out relation based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the sequencing of preset different attribute items.
According to a second aspect of embodiments of the present disclosure, there is provided an apparatus for determining a song list keyword, the apparatus including:
the acquisition module is used for acquiring at least one item of song attribute information of each song included in the target song list;
the first determining module is used for determining at least one attribute descriptor corresponding to each song according to the at least one song attribute information of each song;
the sorting module is used for sorting the at least one item of song attribute information according to a preset sequence, wherein the preset sequence is a paragraph structure;
a second determining module, configured to determine, based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and a preset ordering of different attribute items, a link-in relationship and a link-out relationship between each attribute descriptor and other attribute descriptors;
the third determining module is used for determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors;
the selection module is used for selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors;
and the fourth determining module is used for determining the selected attribute descriptive words as the song list key words of the target song list.
Optionally, the apparatus further comprises:
the second acquisition module is used for acquiring at least one item of song list attribute information of the target song list;
a third determining module, configured to determine at least one attribute descriptor corresponding to the target menu according to the menu attribute information;
the second determining module is configured to determine an in-link relation and an out-link relation between each attribute descriptor and other attribute descriptors based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the attribute item to which the at least one attribute descriptor corresponding to the target menu belongs, and the preset ordering of different attribute items.
Optionally, the first determining module includes:
a first determining unit, configured to determine, as an attribute descriptor corresponding to the song, attribute information in a word form in at least one item of song attribute information of each song;
and the second determining unit is used for performing word segmentation processing on the sentence-form attribute information in at least one item of song attribute information of each song, and determining words obtained through word segmentation as attribute descriptors corresponding to the songs.
Optionally, the third determining module is configured to determine the criticality corresponding to each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
Optionally, the second determining module is configured to:
and determining that at least one attribute descriptor and other attribute descriptors sequenced before the at least one attribute descriptor have a link-in relation and determining that at least one attribute descriptor and other attribute descriptors sequenced after the at least one attribute descriptor have a link-out relation based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the sequencing of preset different attribute items.
According to a third aspect of the embodiments of the present disclosure, there is provided a terminal, which includes a processor and a memory, where at least one instruction, at least one program, a code set, or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the above method for determining a song list keyword.
According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having at least one instruction, at least one program, a set of codes, or a set of instructions stored therein, which is loaded and executed by a processor to implement the above method for determining a song list keyword.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
in the method provided by the embodiment, at least one item of song attribute information of each song included in the target song list is acquired; determining at least one attribute descriptor corresponding to each song according to at least one item of song attribute information of each song; sorting at least one item of song attribute information according to a preset sequence, wherein the preset sequence is a paragraph structure; determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the attribute item to which at least one attribute descriptor corresponding to each song belongs and the preset sequence of different attribute items; determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors; selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors; and determining the selected attribute descriptors as the song menu keywords of the target song menu. In this way, the keywords of the target song list can be selected based on a preset information criticality algorithm. The keywords selected by the algorithm can more accurately describe the characteristics of the target song list than the keywords selected by the user based on the cognition of the user on the song.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. In the drawings:
FIG. 1 is a flow diagram illustrating a method of determining a song menu keyword in accordance with one exemplary embodiment;
FIG. 2 is a schematic diagram illustrating a chaining relationship in accordance with an exemplary embodiment;
fig. 3 is a block diagram illustrating an apparatus for determining a keyword of a song list according to an exemplary embodiment;
fig. 4 is a block diagram illustrating an apparatus for determining a keyword of a song list according to an exemplary embodiment;
fig. 5 is a schematic diagram illustrating a structure of a terminal according to an exemplary embodiment.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The embodiment of the disclosure provides a method for determining a song list keyword, which can be implemented by a terminal. The terminal can be a mobile phone, a tablet computer, a desktop computer, a notebook computer and the like.
The terminal may include a processor, memory, etc. The processor, which may be a CPU (Central Processing Unit), may be configured to determine at least one attribute descriptor corresponding to each song according to at least one item of song attribute information of each song, and perform other Processing. The Memory may be a RAM (Random Access Memory), a Flash (Flash Memory), or the like, and may be configured to store received data, data required by the processing procedure, data generated in the processing procedure, or the like, such as at least one item of song attribute information of each song included in the target song list.
The terminal may also include a transceiver, input components, display components, audio output components, and the like. The transceiver may be configured to perform data transmission with the server, for example, may receive song attribute information of a song sent by the server, and may include a bluetooth component, a WiFi (Wireless-Fidelity) component, an antenna, a matching circuit, a modem, and the like. The input means may be a touch screen, keyboard, mouse, etc. The audio output component may be a speaker, headphones, or the like.
The terminal may have a system program and an application program installed therein. A user uses various applications based on his/her own different needs while using the terminal. The terminal may have an application program with a music playing function installed therein.
An exemplary embodiment of the present disclosure provides a method for determining a song list keyword, as shown in fig. 1, a processing flow of the method may include the following steps:
step S110, at least one item of song attribute information of each song included in the target song list is obtained.
In an implementation, the target song list may be user-created according to his own preference for music, and in the target song list, there may be a plurality of songs that the user puts in. After the target song list is established, keywords need to be added to the target song list, so that other users can simply and clearly know the characteristics of the songs in the target song list when seeing the keywords, and further other users can determine that the other users do not need to listen to the songs in the target song list. The method provided by the embodiment of the disclosure is a method for accurately helping to determine the keywords of the target song list.
The sources of the keywords are song attribute information, song order attribute information, and the like. Song attribute information may include song name, artist name, song language, song zone, song label, artist profile, song movie name, etc. The song list attribute information may include a song list title, a song list description, and the like.
Optionally, the method provided in this embodiment further includes: acquiring at least one item of attribute information of the target song list; and determining at least one attribute descriptive word corresponding to the target song list according to the attribute information of the song list.
In the database, not only a large number of audio files of songs are stored, but also corresponding song attribute information is stored, so that at least one item of song attribute information of each song included in the target menu can be obtained from the database. For the attribute information of the song list, the information can be manually added by the user when the user establishes the target song list, and the attribute information of the song list can be stored after the user manually adds the attribute information of the song list. When the keywords of the target song list are determined, the attribute information of the song list stored in advance can be read out.
And step S120, determining at least one attribute descriptor corresponding to each song according to at least one item of song attribute information of each song.
In the implementation, the song attribute information and the song list attribute information include word form information such as the name of a singer and sentence form information such as the profile of the singer, so that the word form information can be directly used as a candidate word of a keyword without processing. And for the information in the sentence form, word segmentation processing is carried out on the information to segment the information in the sentence form into candidate words of the keywords.
Alternatively, step S120 may include: determining the attribute information in the word form as attribute descriptors corresponding to the songs for the attribute information in the word form in at least one item of song attribute information of each song; and for the sentence-form attribute information in at least one item of song attribute information of each song, performing word segmentation processing on the sentence-form attribute information, and determining words obtained by word segmentation as attribute descriptors corresponding to the songs.
For example, a singer profile for a singer schoolmate is: in 1984 he came out … … for the acquisition of the amateur singing championship in eighteen areas of the first hong kong. The simple medium of the song hand can be subjected to word segmentation processing, and the results of ' 1984 ', ' cause ', ' acquisition ', ' first run ', ' eighteen areas of hong Kong ', ' amateur ', ' singing competition ', ' champion ', ' and ' exit ' are obtained.
And step S130, sorting at least one item of song attribute information according to a preset sequence.
Wherein the predetermined sequence is a paragraph structure. The structure of the paragraph can be as follows:
paragraph 1: singing title
Paragraph 2: description of song list
Paragraph 3: singing bill label
Paragraph 4: song 1: name of song, name of singer, song language, region of song, song label, brief introduction of singer, name of song film and television
Paragraph 5: song 2: name of song, name of singer, song language, region of song, song label, brief introduction of singer, name of song film and television
……
Paragraph N + 3: singer N: name of song, name of singer, song language, region of song, song label, brief introduction of singer, name of song film and television
After the at least one item of song attribute information is sorted according to the preset sequence, a preset number of attribute descriptors with the highest criticality can be selected from all the attribute descriptors according to a preset information criticality algorithm and at least one attribute descriptor corresponding to each song.
Step S140: and determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the attribute item to which at least one attribute descriptor corresponding to each song belongs and the preset sequence of different attribute items.
In implementation, the link-in relationship and the link-out relationship between each attribute descriptor and other attribute descriptors can be determined based on the sequence of the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the attribute item to which the at least one attribute descriptor corresponding to the target song list belongs, and the preset different attribute items.
The attribute items may be song names, singer names, song languages, song regions, song labels, singer profiles, song movie names, song list titles, song list descriptions, and the like. The preset ordering of the different attribute items may be the ordering of the different attribute items as shown in the target document in the embodiment of the present disclosure, that is, the attribute item appearing before is arranged at the front, and the attribute item appearing after is arranged at the back. For example, the name of the song is ranked ahead of the name of the artist, the name of the artist is ranked ahead of the language of the song, and so on. It should be noted that paragraph 1 may be arranged before paragraph 2. In the case of the singer profile, the singer profile is segmented in the foregoing to obtain individual words, and the ordering of the words can be performed according to the word order of the sentence before segmentation.
For the same word, it may be ordered as a word. For example, the singers of song 1 and song 2 are the same person, i.e., the singers of both songs have the same name, and may be ranked as shown in fig. 2, and the song names "slow" and "kiss" may be arranged in front of the singer name "zhangschouyou". Specifically, the ranking may be performed in the order of "song title → singer title → song language → song region → song label", the content of the ranking being "slow, zhuangyou, chinese, hong kong, popular" and "kiss, zhuangyou, chinese, hong kong, lyric". The sorting results are shown in the lower part of fig. 2.
Alternatively, step S140 may include: and determining that at least one attribute descriptor and other attribute descriptors sequenced before the at least one attribute descriptor have a link-in relation and determining that the at least one attribute descriptor and other attribute descriptors sequenced after the at least one attribute descriptor have a link-out relation based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the sequencing of preset different attribute items.
In implementation, after the ordering, the top-ordered attribute descriptors are the chain-in words of the bottom-ordered attribute descriptors, with a chain-in relationship. The attribute descriptors sorted later are the out-links of the attribute descriptors sorted earlier, and have out-links.
And S150, determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation of each attribute descriptor and other attribute descriptors.
In implementation, the criticality corresponding to each attribute descriptor is determined according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors. And selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors.
Alternatively, step S150 may include: determining the corresponding criticality of each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
In implementation, the target words having the in-linking relation with the word whose criticality is to be calculated may be determined first, then the number of the out-linking relations each target word has is determined, the product of the number of the out-linking relations each target word has and the corresponding criticality is determined according to the determined number of the out-linking relations each target word has and the corresponding criticality, all the product results are added, and a preset constant d is substituted to determine S (V) (Vi)。
In equation 1 there is one parameter, S (V)j) Therefore, equation 1 requires iteration multiple times until S (Vi) converges to finally determine S (V)i) The value of (c). In general, one can iterate 20 times, S (V)i) Convergence is possible. In addition, the criticality of all attribute descriptors may be set to 1 at the first iteration. The algorithm described above is a Text-Rank algorithm, and a TF-IDF (term frequency inverse file frequency) algorithm and a Page-Rank algorithm can be used for attribution in the applicationAnd calculating the criticality of the sex descriptors.
Step S160, selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors.
The attribute descriptors with the highest criticality and the preset number have the highest relevance with the target song list and each song in the target song list, and can be used for describing the target song list.
Step S170, the selected attribute descriptive words are determined as the song list key words of the target song list.
In implementation, the attribute descriptors selected by the preset information criticality algorithm can be used as the song list keywords of the target song list.
In the method provided by the embodiment, at least one item of song attribute information of each song included in the target song list is acquired; determining at least one attribute descriptor corresponding to each song according to at least one item of song attribute information of each song; selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors according to a preset information criticality algorithm and at least one attribute descriptor corresponding to each song; and determining the selected attribute descriptors as the song menu keywords of the target song menu. Therefore, the keywords of the target song list can be automatically selected based on a preset information criticality algorithm. The method of selecting keywords through the algorithm has higher efficiency than the method of manually inputting keywords through thinking the keywords.
Yet another exemplary embodiment of the present disclosure provides an apparatus for determining a keyword of a song list, as shown in fig. 3, the apparatus including:
an obtaining module 310, configured to obtain at least one item of song attribute information of each song included in the target song list;
a first determining module 320, configured to determine at least one attribute descriptor corresponding to each song according to the at least one item of song attribute information of each song;
the sorting module 330 is configured to sort the at least one item of song attribute information according to a preset sequence, where the preset sequence is a paragraph structure;
a second determining module 340, configured to determine, based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the preset ordering of different attribute items, a link-in relationship and a link-out relationship between each attribute descriptor and other attribute descriptors;
a third determining module 350, configured to determine, according to the determined link-in relationship and link-out relationship between each attribute descriptor and other attribute descriptors, a criticality corresponding to each attribute descriptor;
the selecting module 360 is configured to select a preset number of attribute descriptors with the highest criticality from all the attribute descriptors;
a fourth determining module 370, configured to determine the selected attribute descriptor as a song list keyword of the target song list.
Optionally, the apparatus further comprises:
the second acquisition module is used for acquiring at least one item of song list attribute information of the target song list;
a third determining module, configured to determine at least one attribute descriptor corresponding to the target menu according to the menu attribute information;
the second determining module is configured to determine an in-link relation and an out-link relation between each attribute descriptor and other attribute descriptors based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the attribute item to which the at least one attribute descriptor corresponding to the target menu belongs, and the preset ordering of different attribute items.
Optionally, as shown in fig. 4, the first determining module 320 includes:
a first determining unit 421, configured to determine, as an attribute descriptor corresponding to the song, attribute information in a word form in at least one item of song attribute information of each song;
a second determining unit 422, configured to perform word segmentation on the sentence-form attribute information in at least one item of song attribute information of each song, and determine a word obtained by word segmentation as an attribute descriptor corresponding to the song.
Optionally, the third determining module 350 is configured to determine the criticality corresponding to each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
Optionally, the second determining module 340 is configured to:
and determining that at least one attribute descriptor and other attribute descriptors sequenced before the at least one attribute descriptor have a link-in relation and determining that at least one attribute descriptor and other attribute descriptors sequenced after the at least one attribute descriptor have a link-out relation based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the sequencing of preset different attribute items.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The keywords of the target song list can be automatically selected based on a preset information criticality algorithm. The method of selecting keywords through the algorithm has higher efficiency than the method of manually inputting keywords through thinking the keywords.
It should be noted that: the apparatus for determining a song list keyword provided in the above embodiment is only illustrated by the division of the above functional modules when determining a song list keyword, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the terminal is divided into different functional modules to complete all or part of the above described functions. In addition, the apparatus for determining the song list keyword and the method embodiment for determining the song list keyword provided by the above embodiment belong to the same concept, and the specific implementation process thereof is detailed in the method embodiment and is not described herein again.
Fig. 5 is a schematic diagram illustrating a structure of a terminal 1800 according to an exemplary embodiment of the present invention. The terminal 1800 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4), a notebook computer, or a desktop computer. The terminal 1800 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, and the like.
Generally, the terminal 1800 includes: a processor 1801 and a memory 1802.
The processor 1801 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 1801 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1801 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 1801 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing content required to be displayed on the display screen. In some embodiments, the processor 1801 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.
In some embodiments, the terminal 1800 may further optionally include: a peripheral interface 1803 and at least one peripheral. The processor 1801, memory 1802, and peripheral interface 1803 may be connected by a bus or signal line. Each peripheral device may be connected to the peripheral device interface 1803 by a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1804, touch screen display 1805, camera 1806, audio circuitry 1807, positioning components 1808, and power supply 1809.
The peripheral interface 1803 may be used to connect at least one peripheral associated with I/O (Input/Output) to the processor 1801 and the memory 1802. In some embodiments, the processor 1801, memory 1802, and peripheral interface 1803 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1801, the memory 1802, and the peripheral device interface 1803 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.
The Radio Frequency circuit 1804 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 1804 communicates with communication networks and other communication devices via electromagnetic signals. The rf circuit 1804 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuitry 1804 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 1804 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: the world wide web, metropolitan area networks, intranets, generations of mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 1804 may also include NFC (Near Field Communication) related circuits, which are not limited in this application.
The display screen 1805 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 1805 is a touch display screen, the display screen 1805 also has the ability to capture touch signals on or over the surface of the display screen 1805. The touch signal may be input to the processor 1801 as a control signal for processing. At this point, the display 1805 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 1805 may be one, providing a front panel of the terminal 1800; in other embodiments, the number of the display screens 1805 may be at least two, and each of the display screens is disposed on a different surface of the terminal 1800 or is in a foldable design; in still other embodiments, the display 1805 may be a flexible display disposed on a curved surface or on a folded surface of the terminal 1800. Even more, the display 1805 may be arranged in a non-rectangular irregular figure, i.e. a shaped screen. The Display 1805 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or the like.
The camera assembly 1806 is used to capture images or video. Optionally, the camera assembly 1806 includes a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 1806 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.
The audio circuitry 1807 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 1801 for processing or inputting the electric signals to the radio frequency circuit 1804 to achieve voice communication. The microphones may be provided in a plurality, respectively, at different positions of the terminal 1800 for the purpose of stereo sound collection or noise reduction. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 1801 or the radio frequency circuitry 1804 to sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, audio circuitry 1807 may also include a headphone jack.
The positioning component 1808 is utilized to locate a current geographic position of the terminal 1800 for navigation or LBS (Location Based Service). The Positioning component 1808 may be a Positioning component based on a Global Positioning System (GPS) in the united states, a beidou System in china, or a galileo System in russia.
The power supply 1809 is used to power various components within the terminal 1800. The power supply 1809 may be ac, dc, disposable or rechargeable. When the power supply 1809 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery charged through a wired line, and the wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charge technology.
In some embodiments, the terminal 1800 also includes one or more sensors 1810. The one or more sensors 1810 include, but are not limited to: acceleration sensor 1811, gyro sensor 1812, pressure sensor 1813, fingerprint sensor 1814, optical sensor 1815, and proximity sensor 1816.
The acceleration sensor 1811 may detect the magnitude of acceleration on three coordinate axes of a coordinate system established with the terminal 1800. For example, the acceleration sensor 1811 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 1801 may control the touch display 1805 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 1811. The acceleration sensor 1811 may also be used for acquisition of motion data of a game or a user.
The gyro sensor 1812 may detect a body direction and a rotation angle of the terminal 1800, and the gyro sensor 1812 may cooperate with the acceleration sensor 1811 to collect a 3D motion of the user on the terminal 1800. The processor 1801 may implement the following functions according to the data collected by the gyro sensor 1812: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.
The pressure sensors 1813 may be disposed on a side bezel of the terminal 1800 and/or on a lower layer of the touch display 1805. When the pressure sensor 1813 is disposed on a side frame of the terminal 1800, a user's grip signal on the terminal 1800 can be detected, and the processor 1801 performs left-right hand recognition or shortcut operation according to the grip signal collected by the pressure sensor 1813. When the pressure sensor 1813 is disposed at the lower layer of the touch display screen 1805, the processor 1801 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 1805. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.
The fingerprint sensor 1814 is used to collect the fingerprint of the user, and the processor 1801 identifies the user according to the fingerprint collected by the fingerprint sensor 1814, or the fingerprint sensor 1814 identifies the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the processor 1801 authorizes the user to perform relevant sensitive operations, including unlocking a screen, viewing encrypted information, downloading software, paying, and changing settings, etc. The fingerprint sensor 1814 may be disposed on the front, back, or side of the terminal 1800. When a physical key or vendor Logo is provided on the terminal 1800, the fingerprint sensor 1814 may be integrated with the physical key or vendor Logo.
The optical sensor 1815 is used to collect the ambient light intensity. In one embodiment, the processor 1801 may control the display brightness of the touch display 1805 based on the ambient light intensity collected by the optical sensor 1815. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 1805 is increased; when the ambient light intensity is low, the display brightness of the touch display 1805 is turned down. In another embodiment, the processor 1801 may also dynamically adjust the shooting parameters of the camera assembly 1806 according to the intensity of the ambient light collected by the optical sensor 1815.
A proximity sensor 1816, also known as a distance sensor, is typically provided on the front panel of the terminal 1800. The proximity sensor 1816 is used to collect the distance between the user and the front surface of the terminal 1800. In one embodiment, when the proximity sensor 1816 detects that the distance between the user and the front surface of the terminal 1800 gradually decreases, the processor 1801 controls the touch display 1805 to switch from the bright screen state to the dark screen state; when the proximity sensor 1816 detects that the distance between the user and the front surface of the terminal 1800 becomes gradually larger, the processor 1801 controls the touch display 1805 to switch from the breath screen state to the bright screen state.
Those skilled in the art will appreciate that the configuration shown in fig. 5 is not intended to be limiting of terminal 1800 and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method of determining a keyword of a song list, the method comprising:
acquiring at least one item of song attribute information of each song included in a target song list;
determining at least one attribute descriptor corresponding to each song according to the at least one item of song attribute information of each song;
sorting the at least one item of song attribute information according to a preset sequence, wherein the preset sequence is a paragraph structure;
based on the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the sequencing of preset different attribute items, sequencing the at least one attribute descriptor corresponding to each song according to the sequencing sequence of the preset different attribute items, and determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors;
determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors;
selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors;
determining the selected attribute descriptors as the song menu keywords of the target song menu;
wherein, the determining the link-in relation and the link-out relation of each attribute descriptor and other attribute descriptors comprises: determining that at least one attribute word and other attribute descriptors ordered before the at least one attribute word have a link-in relationship, and determining that the at least one attribute descriptor and other attribute descriptors ordered after the at least one attribute descriptor have a link-out relationship.
2. The method of claim 1, further comprising:
acquiring at least one item of attribute information of the target song list;
determining at least one attribute descriptor corresponding to the target song list according to the attribute information of the song list;
the sequencing at least one attribute descriptor corresponding to each song according to the preset sequencing order of different attribute items and determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the sequencing of the attribute item to which the at least one attribute descriptor corresponding to each song belongs and the preset different attribute items comprises the following steps:
and sequencing the at least one attribute descriptor corresponding to each song according to the sequencing sequence of the preset different attribute items and determining the link-in relation and the link-out relation between each attribute descriptor and other attribute descriptors based on the sequencing of the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the sequencing of the attribute item to which the at least one attribute descriptor corresponding to the target menu belongs and the preset different attribute items.
3. The method according to claim 1, wherein the determining at least one attribute descriptor corresponding to each song according to the at least one item of song attribute information of each song comprises:
determining the attribute information in the word form as attribute descriptors corresponding to the songs for the attribute information in the word form in the at least one item of song attribute information of each song;
and for the sentence-form attribute information in at least one item of song attribute information of each song, performing word segmentation on the sentence-form attribute information, and determining words obtained by word segmentation as attribute descriptors corresponding to the songs.
4. The method according to claim 1, wherein determining the criticality corresponding to each attribute descriptor according to the determined in-link relation and out-link relation of each attribute descriptor and other attribute descriptors comprises:
determining the corresponding criticality of each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
5. An apparatus for determining a keyword of a song list, the apparatus comprising:
the acquisition module is used for acquiring at least one item of song attribute information of each song included in the target song list;
the first determining module is used for determining at least one attribute descriptor corresponding to each song according to the at least one song attribute information of each song;
the sorting module is used for sorting the at least one item of song attribute information according to a preset sequence, wherein the preset sequence is a paragraph structure;
a second determining module, configured to rank, based on a ranking of an attribute item to which at least one attribute descriptor corresponding to each song belongs and preset different attribute items, the at least one attribute descriptor corresponding to each song according to a sequence of the preset different attribute items, and determine a link-in relationship and a link-out relationship between each attribute descriptor and other attribute descriptors;
the third determining module is used for determining the corresponding criticality of each attribute descriptor according to the determined link-in relation and link-out relation between each attribute descriptor and other attribute descriptors;
the selection module is used for selecting a preset number of attribute descriptors with the highest criticality from all the attribute descriptors;
the fourth determining module is used for determining the selected attribute descriptive words as the song menu key words of the target song menu;
wherein, the determining the link-in relation and the link-out relation of each attribute descriptor and other attribute descriptors comprises: determining that at least one attribute word and other attribute descriptors ordered before the at least one attribute word have a link-in relationship, and determining that the at least one attribute descriptor and other attribute descriptors ordered after the at least one attribute descriptor have a link-out relationship.
6. The apparatus of claim 5, further comprising:
the second acquisition module is used for acquiring at least one item of song list attribute information of the target song list;
a third determining module, configured to determine at least one attribute descriptor corresponding to the target menu according to the menu attribute information;
the second determining module is configured to rank, based on the ranking of the attribute item to which the at least one attribute descriptor corresponding to each song belongs, the attribute item to which the at least one attribute descriptor corresponding to the target menu belongs, and preset different attribute items, the at least one attribute descriptor corresponding to each song according to the ranking order of the preset different attribute items, and determine a link-in relationship and a link-out relationship between each attribute descriptor and other attribute descriptors.
7. The apparatus of claim 5, wherein the first determining module comprises:
a first determining unit, configured to determine, as an attribute descriptor corresponding to the song, attribute information in a word form in at least one item of song attribute information of each song;
and the second determining unit is used for performing word segmentation processing on the sentence-form attribute information in at least one item of song attribute information of each song, and determining words obtained through word segmentation as attribute descriptors corresponding to the songs.
8. The apparatus of claim 5, wherein the third determining module is configured to:
determining the corresponding criticality of each attribute descriptor according to the following formula:
wherein, S (V)i) Describing the word V for any attributeiThe criticality of (c); d is a preset constant; in (V)i) Descriptor V for and attributeiAttribute descriptors with chaining-in relationships; | Out (V)j) I is an attribute descriptor VjThe number of attribute descriptors with a linked-out relationship; s (V)j) Describing words V for attributesjThe criticality of (a).
9. A terminal, characterized in that the terminal comprises a processor and a memory, in which at least one instruction, at least one program, a set of codes or a set of instructions is stored, which is loaded and executed by the processor to implement the method of determining a song list keyword according to any one of claims 1-4.
10. A computer readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by a processor to implement the method of determining a song list keyword according to any one of claims 1 to 4.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164471A (en) * | 2011-12-15 | 2013-06-19 | 盛乐信息技术（上海）有限公司 | Recommendation method and system of video text labels |
| CN105893571A (en) * | 2016-03-31 | 2016-08-24 | 乐视控股（北京）有限公司 | Method and system for establishing content tag of video |
| CN106446135A (en) * | 2016-09-19 | 2017-02-22 | 北京搜狐新动力信息技术有限公司 | Method and device for generating multi-media data label |
| WO2017070427A1 (en) * | 2015-10-23 | 2017-04-27 | Spotify Ab | Automatic prediction of acoustic attributes from an audio signal |
| CN106874362A (en) * | 2016-12-30 | 2017-06-20 | 中国科学院自动化研究所 | Multilingual automaticabstracting |
| CN107193878A (en) * | 2017-04-24 | 2017-09-22 | 维沃移动通信有限公司 | It is a kind of to sing single automatic naming method and mobile terminal |
| CN107766318A (en) * | 2016-08-17 | 2018-03-06 | 北京金山安全软件有限公司 | Keyword extraction method and device and electronic equipment |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7996392B2 (en) * | 2007-06-27 | 2011-08-09 | Oracle International Corporation | Changing ranking algorithms based on customer settings |
| CN102622451A (en) * | 2012-04-16 | 2012-08-01 | 上海交通大学 | System for automatically generating television program labels |
| CN107180075A (en) * | 2017-04-17 | 2017-09-19 | 浙江工商大学 | The label automatic generation method of text classification integrated level clustering |
-
2018
- 2018-03-21 CN CN201810235861.6A patent/CN108446276B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164471A (en) * | 2011-12-15 | 2013-06-19 | 盛乐信息技术（上海）有限公司 | Recommendation method and system of video text labels |
| WO2017070427A1 (en) * | 2015-10-23 | 2017-04-27 | Spotify Ab | Automatic prediction of acoustic attributes from an audio signal |
| CN105893571A (en) * | 2016-03-31 | 2016-08-24 | 乐视控股（北京）有限公司 | Method and system for establishing content tag of video |
| CN107766318A (en) * | 2016-08-17 | 2018-03-06 | 北京金山安全软件有限公司 | Keyword extraction method and device and electronic equipment |
| CN106446135A (en) * | 2016-09-19 | 2017-02-22 | 北京搜狐新动力信息技术有限公司 | Method and device for generating multi-media data label |
| CN106874362A (en) * | 2016-12-30 | 2017-06-20 | 中国科学院自动化研究所 | Multilingual automaticabstracting |
| CN107193878A (en) * | 2017-04-24 | 2017-09-22 | 维沃移动通信有限公司 | It is a kind of to sing single automatic naming method and mobile terminal |
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|---|---|
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Effective date of registration: 20230526 Address after: 518000 Room 201, building A, 1 front Bay Road, Shenzhen Qianhai cooperation zone, Shenzhen, Guangdong Patentee after: TENCENT MUSIC ENTERTAINMENT (SHENZHEN) Co.,Ltd. Address before: 518000 Room 201, building A, 1 front Bay Road, Shenzhen Qianhai cooperation zone, Shenzhen, Guangdong Patentee before: TENCENT MUSIC ENTERTAINMENT TECHNOLOGY (SHENZHEN) Co.,Ltd. |