JP2008191768A - RECOMMENDED INFORMATION PROCESSING SYSTEM AND RECOMMENDED INFORMATION PROCESSING METHOD - Google Patents

Abstract

Content information adapted to individual user preferences, including the latest information, can be recommended without leaking personal information.
Each terminal device 1 includes a network connection unit 20 for connecting to an SNS network group, a content processing unit 10 for extracting user preference information and recommendation information from content use / purchase information, and an SNS. A recommendation information transmission / reception unit 40 that provides recommendation information to other terminal devices via the type network and obtains recommendation information from other terminal devices, and a recommendation information display unit 50 that displays the obtained recommendation information on the display unit 4 Is provided.
[Selection] Figure 1

Description

  The present invention relates to a recommended information processing system and a recommended information processing method for providing content recommendation information between terminal devices via a network or the like.

Conventionally, there are the following techniques for recommending and introducing information between users (terminal devices) via a network or the like.
(1) Teaching product information and URLs on the Internet using e-mail and introducing contents such as newly published magazines and TV programs.
(2) Collecting and analyzing information on contents purchased by a plurality of users and information on contents used, and recommending contents such as magazines and television programs.
(3) For each user, information on contents purchased in the past, information on contents used, and the like are accumulated, and contents purchased / used by other users with similar preferences are introduced (Patent Document 1, Patent Document) 2).

(4) While a user is watching a program, a specific scene to be introduced is introduced to another arbitrary viewer (Patent Document 3).
(5) When the user specifies a desired content, recommendation information of the genre is obtained.
(6) The content provider accumulates purchase information, usage information, and the like for each user, and the content provider recommends content according to the preference for each user.
(7) A content provider collects and accumulates purchase information and usage information of users, and recommends popular content (high frequency of use and purchase) to users.

JP 2000-187666 A JP 2005-56531 A JP 2002-218428 A

Although it is desired that the information to be recommended / introduced is suitable for each user's preference, the above technique has the following problems.
(1) The recommendation method by e-mail only introduces product information and URLs on the Internet, and cannot recommend content that suits individual user preferences.
(2) In a recommendation method for collecting and analyzing information on contents purchased by a plurality of users in the past, information on contents used, etc., new publications and topical contents cannot be recommended because of past information.
(3) In a recommendation method that uses information on content purchased in the past or information on content used for each user, since past preferences for each user are estimated, genres that have never been used or purchased in the past Content or topical content cannot be recommended. In addition, the information provider is not a user's acquaintance, but rather a person who does not know at all. Therefore, the recommended information often does not match the user's preference, and the number of useful samples is small. In addition, information such as the purchase history of content is taught to a person who does not know at all from the user who provides the information, and there is a concern that personal information may be leaked.

(4) In the recommendation method in which a user identifies and introduces a scene to other users, the latest information can be recommended, but the information is not necessarily in accordance with the other user's preference. Absent. That is, the recommender does not recommend in consideration of the other user's preference.
(5) In a recommendation method in which recommended information for a genre is obtained by designating a desired content by a user, desired recommendation information cannot be obtained unless the user designates the content properly.
(6) In a recommendation method in which a content provider stores user purchase information / use information and recommends content in accordance with user preferences, the recommendation method is limited to information about the content handled by the provider.
(7) When a content provider collects and accumulates purchase information and usage information of users and recommends popular content, the recommended information does not match the preferences of individual users.

  As described above, in each of the conventional techniques, it is difficult to recommend a large amount of information including the latest information that matches the user's personal preference. There is also a concern that personal information may leak between users who do not know each other. Therefore, even if the above technologies are combined, it is difficult to provide active information among users with similar tastes, and it is considered that there is a problem in the network form to which users subscribe. That is, when providing recommendation information to a plurality of users who have a good taste, it is difficult to take in and use recommendation information introduced by a third user outside the network.

  The present invention has been made in view of the problems as described above, and recommend information that can recommend content information suitable for each user's preference, including the latest information, without leaking personal information. It is an object to provide a processing system and a recommended information processing method.

  In the recommended information processing system of the present invention, each terminal device is connected to a social networking service type (hereinafter referred to as SNS) network group, and user preference information and recommendation from content use / purchase information. A content processing unit for extracting information, a recommendation information transmission / reception unit for providing recommendation information to other terminal devices via the SNS network, and obtaining recommendation information from the other terminal devices, and the obtained recommendation information on the display unit A recommendation information display unit to be displayed.

  The network connection unit includes an SNS type network group group creating unit, an invitation unit for inviting another terminal device to the SNS type network group, an authentication unit for participating in the SNS type network group, and an SNS type network. Includes means to join the group.

  Then, the recommendation information obtained by the recommendation information transmission / reception unit is analyzed based on the preference information extracted by the content processing unit and the recommendation information, and the recommendation information display unit converts the obtained recommendation information into user preference information. Display in a combined format.

  The recommendation information processing method of the present invention connects each terminal device to a social networking service type network group, and each terminal device extracts user preference information and recommendation information from content use / purchase information, and extracts the recommendation Information is provided to other terminal devices via the SNS network, recommendation information is obtained from the other terminal devices, and the obtained recommendation information is displayed on the display unit.

  Here, the terminal device connected to the SNS network group has a function of inviting other terminal devices that are not connected to connect to the SNS network group.

  According to the present invention, it is possible to recommend content information suitable for each user's preference without leaking personal information including the latest information.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. The content targeted by the recommended information processing system of the present invention can be viewed or purchased by the user and used. This includes multimedia content such as TV programs, movies, photos, videos, music (including music distribution), products such as books, videos, CDs, DVDs, news information, Web pages, blogs, and SNS information sites. Internet content, etc. In addition, information on cooking and cooking recipes, restaurants and liquor, ski resorts / amusement parks / zoos / attractions, etc. are included.

  FIG. 1 is a block diagram showing an embodiment of a recommended information processing system according to the present invention. In this system, each user (each terminal device) uses a social networking service (hereinafter abbreviated as SNS) type network group to participate in the network group. Each user provides preference / recommendation information to other users (other terminal devices) via the SNS network, and obtains preference / recommendation information from other users. Here, a TV program will be described as an example of content.

  The recommended information processing terminal device 1 is configured based on, for example, a personal computer or a TV that receives and views a television program. The overall configuration includes a content processing unit 10 that inputs content and extracts recommendation information, a network connection unit 20 that participates and connects to an SNS network group, a recording device 30 that records and stores content and recommendation information, and a network. A recommendation information transmission / reception unit 40 that provides recommendation information to other terminal devices and obtains recommendation information from other terminal devices, and a recommendation information display unit 50 that analyzes and displays the obtained recommendation information.

  The input unit 2 is a part that reproduces and inputs a television program from an antenna that receives the television program as content or a recording medium such as a memory or a hard disk. The communication unit 3 is connected to an Internet line or the like and transmits / receives information to / from other terminal devices. In addition to the Internet line, the communication unit 3 may be via a local network, via a Web page, via a server, or via another terminal. Content can also be obtained from the outside through the communication unit 3. The display unit 4 is a display or a speaker that displays the acquired content and recommendation information. The input unit 2, the communication unit 3, and the display unit 4 can also be configured as a part of the recommended information processing terminal device 1.

Hereinafter, each part will be described.
In the content processing unit 10, the content input unit 11 records and accumulates the content (television program) obtained through the input unit 2 or the communication unit 3 as the content 31 in the recording device 30.
In the content list input unit 12, the TV program information (EPG), which is content information obtained through the input unit 2 or the communication unit 3, and a content list in which the content information is collected are recorded as a content list 32 in the recording device 30.

  In the content use / purchase information storage means 13, information on television programs and recorded programs viewed by the user (including recording reservation / viewing time use information using EPG) is stored in the recording device 30 as content use / purchase information 33. Record as. When recommending a television program in this system, EPG can be used. Since the EPG can always be obtained by receiving it through the Internet or an antenna, the recommended information is always the latest.

  The preference / recommendation information extraction unit 14 extracts user preference information and recommendation information based on the usage status of the content 31 stored in the recording device 30. In that case, a user's preference can be extracted automatically using the existing preference extraction method. Alternatively, preference / recommendation information is extracted by designating content that the user wants to recommend (in contrast, it is possible to designate content that the user does not want to recommend).

  The preference / recommendation information storage unit 15 records the user's own preference / recommendation information 34 extracted by the preference / recommendation information extraction unit 14 in the recording device 30. At that time, it is better to save the information in a list.

  The network connection unit 20 has an SNS type network group utilization function, and includes an SNS type network group creation unit 21, an SNS type network group invitation unit 22, an SNS type network group authentication unit 23, and an SNS type network group participation unit 24. By using the SNS network group function, the group participants (terminals connected to the group) have the function to invite other users (terminals not connected to the group), and at the same time, invited users A person can also invite other users. In this way, it is possible to increase the number of participants (connection terminals) to the network group. This feature will be described later.

  In the recommendation information transmission / reception unit 40, the preference / recommendation information input / output means 41 transmits / receives preference / recommendation information between the user (terminal device 1) and the SNS network group participant (other terminal devices). That is, the preference / recommendation information of the participant is received from the communication unit 3, and the preference / recommendation information of the user himself / herself is transmitted from the communication unit 3 to the participant. The preference / recommendation information to be transmitted is read from the user's preference / recommendation information 34 stored in the recording device 30, and the received preference / recommendation information of the participant is stored in the recording device 30 as the preference / recommendation information 35 of the network group. To do.

  The content use / purchase information input / output unit 42 transmits / receives use / purchase information via the communication unit 3 between the user (terminal device 1) and the SNS network group participant (other terminal device). . The transmitted / received usage / purchase information is stored in the recording device 30.

  The preference / recommendation information collection / accumulation means 43 organizes and collects the preference / recommendation information received from the SNS network group participants (other terminal devices) so that the broadcast program / broadcast time (scheduled time) can be understood. The information is collected as a list and recorded in the recording device 30 as network group preference / recommendation information 35.

  In the recommendation information display section 50, the preference / recommendation information analysis means 51 is based on the preference / recommendation information 35 of the network group stored in the recording device 30 and the preference / recommendation information 34 of the user himself / herself. Analyzes stations, highly recommended TV programs, etc.

  The preference / recommendation information display means 52 sends the preference / recommendation information analyzed by the preference / recommendation information analysis means 51 to the display unit 4 for display. At this time, a program with a high recommendation degree or a program close to the user's preference is displayed in a more easily viewable manner by distinguishing it from other programs.

  Each of the above means can be realized by installing a software program in a computer included in the recommended information processing system. These programs are stored in a recording medium such as a memory device or a hard disk that can be read by a computer, and read and executed as needed.

  As described above, in the recommended information processing system according to the present embodiment, content preference / recommendation information is mutually provided among the participants (connected terminal devices) of the SNS network group, and the obtained preference / recommendation information is provided to the user. By analyzing the recommendation ranking based on the user's preference tendency, it is possible to acquire information that matches the user's preference.

  FIG. 2 is a diagram showing functions of the SNS type network group used in the present system. (A) shows the function of the conventional network group A for comparison, and this includes user a, user b, user c, and user d as group members (terminal devices connected to the group). Suppose you are participating. When the user c who is one of the members invites the user x, which is a non-member (unconnected terminal device), to the group, the user x can communicate with the user c, but communicates with other members. Can not. That is, since it cannot participate in the network group A, recommendation information cannot be provided with other members.

  On the other hand, (b) shows the function of the SNS network group B. Similarly, user a, user b, user c, and user d participate as group members (terminal devices connected to the group). Suppose that When the user c who is one of the members invites the user x who is a non-member (unconnected terminal device) to the group, the user x can communicate with not only the user c but all other members. In other words, it is possible to participate in the network group A and provide recommendation information with other members.

  By having the SNS network group function in this way, the group participant (connected terminal) has a function of inviting other users (non-connected terminals), and at the same time, the invited user is further added to other users. By inviting (unconnected terminals), it is possible to add a network group participant and expand the group.

By this function, the following effects can be obtained.
(1) It is easy to configure a group centered on the user's acquaintances and indirect acquaintances, and conversely, other users who are completely unaware of the user rarely become group members. Therefore, it is possible to reduce the risk of personal information (user's own information and information such as which program the user is watching) being leaked to a third party and misused.
(2) It is easy to create a genre-limited network group. For example, it is assumed that an SNS type network group that likes romance dramas is created with limited genres. You can invite other users who love romance dramas by providing recommended information on programs that are currently in the romance dramas and new programs in romance dramas, and the invited users like romance dramas Other users can be invited, and network groups that love dramas will expand. In this case, the user's preference (love drama lover) is retained, and the recommendation information outside the preference that causes noise is excluded, so that the recommendation information more suitable for the user's preference is provided.
(3) Even in the SNS network, it is also possible to obtain preference / recommendation information of all users when all users participate in the network group. For TV programs, preference / recommendation information such as programs with high audience rating and usage rate can be obtained.

FIG. 3 is a flowchart showing the group creation processing procedure of the SNS network group creation means 21 in this system.
The user makes a request to create a new SNS network group (S101). Then, the name and characteristics of the network group (eg, love drama group, talent ** group, ** university group, etc.) are input (S102, S103). A confirmation message “Can I create a network group?” Is displayed (S104), and if it is to be created, it is accepted (Yes in S104). Then, a network group unique key (ID) for identifying the network group to be created is acquired (S105), and a new network group is created (S106). As a network group unique key for identifying a network group, a unique key is created using an existing encryption technique or key generation technique.

  FIG. 4 is a flowchart showing the group invitation processing procedure of the SNS network group invitation means 22 in this system. Here, as shown in FIG. 2, it is assumed that a user (connected terminal) c participating in the group invites another user (non-connected terminal) x not participating in the group.

  First, personal information of another user x known by the user c is obtained (S201). The user c makes an invitation request to the SNS network group so that the user x can participate (S202), and inputs information about the user x (S203). A confirmation message “Can I invite you to join the network group?” Is displayed (S204), and if accepted (Yes in S204), the user x is invited to the network group (S205). The information of the user c who is the introducer and the information of the network group to which the introducer belongs are provided to other users x (S206, S207). Then, a confirmation message “Do you want to join the network group?” Is displayed to the user x (S208). If the user x accepts this (Yes in S208), information such as a network group unique key for identifying the network group is provided to the user x (S209), thereby enabling participation in the network group. .

  In the SNS type network group authentication means 23 and participation means 24 of this system, it is determined whether or not the network group is a member of the network group from the network group name or the network group unique key for identifying the network group. Allow users to join and log in to groups.

  By the way, in order to make the preference / recommendation information provided via the SNS network group more effective, when the network group is created, a participant condition (for example, age condition) is set to restrict the participant. In order to narrow down the preference / recommendation information provided. Also, when creating a network group, it is possible to specify a specific genre (for example, fashion-related or cooking-related), collect people with the same hobbies, or give specific keywords (specific celebrities, specific animals, etc.) By doing so, it becomes possible to provide preference / recommendation information that matches the preferences of all the participants and matches the preferences of the users.

  In the recommended information processing system according to the present embodiment, a user who belongs to an SNS network group generally provides preference / recommendation information to all participants who belong to the group. In this case, since the participants of the SNS network group are persons who know each other directly or indirectly, personal information (information about the user himself / herself and which program the user is watching) is the first. It can be said that there is little risk of leakage to the three parties and misuse. However, there are cases where it is desired to limit the information providing destination even for participants in the same network group. In that case, it is possible to specify the participants who may provide the information or the participants who do not want to provide the information, and limit the destination of the preference / recommendation information. It is also possible to limit the types of content to be provided. In other words, the user's privacy can be protected by designating a television program that may provide information (for example, a news program) and a program that does not want to provide information (for example, an English conversation program).

  In the first embodiment, how to provide recommendation information has been described by taking a television program as an example of content. Various other types of content are possible, but a specific example in the case where the content is a book will be described.

  FIG. 5 is an example of the content information 31 when the content is a book. In the case of a book, any information (such as a publishing office, a release date, a sale title, etc.) that identifies the book may be used. As a similar content, in the case of a movie, information that can be distinguished from other movies such as a screening title, a performer, and a screening start date may be used.

  FIG. 6 is an example of the content list 32 in the case of a book. The content list in which content information is collected is a list of content information 31. At that time, the latest information can be recommended at all times by distinguishing between a new publication list and a latest screening list for movies.

  FIG. 7 is an example of the content use / purchase information 33. It is convenient for the usage / purchase information of a book to include not only the title of the book but also a method for obtaining the book (for example, purchase by reservation, purchase online, purchase at a store, currently being reserved for purchase). At that time, information on popular stores and stores scheduled to open is also useful. In addition, when the use / purchase is planned for a pre-release book, more up-to-date recommendation information can be provided.

  FIG. 8 shows various methods for extracting the preference / recommendation information of the user by the preference / recommendation information extraction means 14. Among them, a method of extracting preference from content frequently used by users and creating recommendation information is effective.

FIG. 9 is an example of preference / recommendation information 34 in the case of a book. User preference / recommendation information extracted by the preference / recommendation information extraction means 14 is displayed in a list.
The preference / recommendation information 34 created in this way is provided to other users (terminal devices) via the network.

  FIG. 10 is an example of the preference / recommendation information 35 obtained from the network group. The preference / recommendation information collection / accumulation means 43 organizes the acquired information together with the name of the recommender and recommendation information (book usage status), and stores the information in a list.

  FIGS. 11 to 13 show some examples of analyzing the obtained preference / recommendation information and displaying it on the display unit 4. FIG. 11 shows a case where the obtained recommendation information is displayed as a list in order of highest recommendation level ranking (or in descending order of user preference). FIG. 12 shows a case where a user's preference is highlighted (further icons are added, font / color is changed, etc.). FIG. 13 shows a case where the recommendation level is displayed by the number of marks (★). Information of a recommender indicating who is recommending is also added to these.

  By appropriately switching these display methods, it is possible to clearly display the recommendation information in a format that matches not only the recommendation level of each content but also the user's preference.

  According to each embodiment described above, by creating an SNS network group, it becomes possible to provide information between users who know directly or indirectly, and personal information is leaked and misused. There is no fear. In addition, by creating a genre-limited network group, it is possible to obtain content recommendation information that suits individual user preferences. You can also get the latest recommendation information, including pre-release content.

The block block diagram which shows one Example of the recommendation information processing system concerning this invention. The figure which shows the function of the SNS type network group utilized with this system. The flowchart which shows the process sequence of a SNS type | mold network group preparation means. The flowchart which shows the process sequence of an SNS type network group invitation means. The figure which shows the example of the content information in case a content is a book. The figure which shows the example of a content list in case a content is a book. The figure which shows the example of content utilization / purchase information. The figure which shows the various methods of extracting a user's preference and recommendation information. The figure which shows the example of the preference and recommendation information in the case of a book. The figure which shows the example of the preference and recommendation information acquired from the network group. The figure which shows the example which displayed the acquired recommendation information in order of recommendation degree ranking. The figure which shows the example which highlighted and displays the acquired recommendation information near preference. The figure which shows the example which displayed the recommendation degree of the acquired recommendation information by the number of marks.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Recommended information processing terminal device 2 ... Input part 3 ... Communication part 4 ... Display part 10 ... Content processing part 11 ... Content input means 12 ... Content list input means 13 ... Content utilization / purchase information storage means 14 ... Preference / recommendation information Extraction means 15 ... preference / recommendation information storage means 20 ... network connection unit 21 ... SNS type network group creation means 22 ... SNS type network group invitation means 23 ... SNS type network group authentication means 24 ... SNS type network group participation means 30 ... recording Apparatus 40 ... Recommendation information transmission / reception unit 41 ... Preference / recommendation information input / output means 42 ... Content use / purchase information input / output means 50 ... Recommendation information display part 51 ... Preference / recommendation information analysis means 52 ... Preference / recommendation information display means.

Claims (5)

In a recommendation information processing system that provides content recommendation information between terminal devices connected to a network,
Each of the above terminal devices
A network connection unit for connecting to a social networking service type (hereinafter referred to as SNS) network group;
A content processing unit that extracts user preference information and recommendation information from content use / purchase information;
A recommendation information transmission / reception unit for providing recommendation information to other terminal devices via the SNS network and obtaining recommendation information from other terminal devices;
A recommendation information processing system comprising: a recommendation information display unit for displaying the obtained recommendation information on a display unit. The recommended information processing system according to claim 1,
The network connection unit
Means for creating an SNS network group;
Invitation means for inviting other terminal devices to the SNS network group;
An authentication means for participating in the SNS network group;
A recommended information processing system comprising means for participating in an SNS network group. The recommended information processing system according to claim 1,
The recommendation information obtained by the recommendation information transmission / reception unit is analyzed based on the preference information and recommendation information extracted by the content processing unit, and the recommendation information display unit matches the obtained recommendation information with the user's preference information. A recommended information processing system characterized by being displayed in a format. In a recommended information processing method for providing content recommendation information between terminal devices connected to a network,
Connect each terminal device to a social networking service type (hereinafter referred to as SNS) network group,
Each terminal device extracts user preference information and recommendation information from content use / purchase information,
Providing the extracted recommendation information to other terminal devices via the SNS network and obtaining recommendation information from other terminal devices;
A recommended information processing method for displaying the obtained recommended information on a display unit. The recommended information processing method according to claim 4,
The recommended information processing method, wherein the terminal device connected to the SNS network group invites other terminal devices not connected to connect to the SNS network group.

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