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CN118761390B - Method for hiding knowledge in text file for independent or combined reading based on AI technology - Google Patents

Method for hiding knowledge in text file for independent or combined reading based on AI technology Download PDF

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CN118761390B
CN118761390B CN202411216100.8A CN202411216100A CN118761390B CN 118761390 B CN118761390 B CN 118761390B CN 202411216100 A CN202411216100 A CN 202411216100A CN 118761390 B CN118761390 B CN 118761390B
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CN118761390A (en
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蔡亚军
于晓丽
何冉冉
何中
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Jiangsu Zhongwei Technology Software System Co ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/166—Editing, e.g. inserting or deleting
    • G06F40/169—Annotation, e.g. comment data or footnotes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
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    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/103—Formatting, i.e. changing of presentation of documents
    • G06F40/109—Font handling; Temporal or kinetic typography
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/103—Formatting, i.e. changing of presentation of documents
    • G06F40/117—Tagging; Marking up; Designating a block; Setting of attributes

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Abstract

The invention discloses a method for hiding knowledge in text files for independent or combined reading based on an AI technology, which comprises the following steps: the method comprises the steps of setting a knowledge matching base, analyzing and judging the type of the uploaded file; analyzing the file to obtain the type of the field to which the file belongs; according to the field type of the file, analyzing the file to obtain a text queue to be expanded, inputting the queue into a knowledge model, and obtaining a key and value key value pair model in one-to-one correspondence; the method effectively fuses the knowledge in the file by using the AI technology and the OFD expansion file, creates a method for hiding the knowledge in the file, and processes the file by using the technology so that a large amount of knowledge content is attached to the original file, thereby improving the reading experience of readers and improving the reading efficiency.

Description

Method for hiding knowledge in text file for independent or combined reading based on AI technology
Technical Field
The technology belongs to the technical field of artificial intelligence, and in particular relates to a method for hiding knowledge in text files for independent or combined reading by an AI technology.
Background
When the traditional electronic file is read, the read content is limited to the file itself, some expansion or association matching can not be carried out on the file itself, and compared with a webpage, remarks are required to be added during maintenance, and automatic remarks, marks or judgment can not be carried out; and the file reading is online matching inquiry and can not be checked offline.
Disclosure of Invention
The present invention is directed to a method for hiding knowledge from text files by AI technology for independent or combined reading, so as to solve one or more of the problems set forth in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: the method for hiding knowledge in text files for independent or combined reading based on AI technology comprises the following steps:
step S1: setting a knowledge matching base;
Step S2: analyzing and judging the uploaded file type, and if the file type is not the standard OFD file, converting the file type into the standard OFD file;
step S3: analyzing the file by using the NLP to acquire the field type of the file, and matching the universal data in the knowledge matching base if the field type of the file cannot be judged;
step S4: according to the file field type, analyzing and acquiring file content information to obtain a text queue to be expanded, inputting the text queue into a knowledge model, and acquiring a key and value key value pair model in one-to-one correspondence;
Step S5: typesetting the association relation information between the content (key) of the recorded original text and the interpretation (value) of the original text according to a format to form a knowledge base xml file, generating an expansion file package of the OFD, and generating a new OFD file which can be used for online or offline transmission and reading;
Step S6: and loading an original file of the OFD file by using the OFD reader for reading, analyzing the knowledge expansion file package if the original file has the knowledge expansion file package, displaying the content identification appointed by the original file, and displaying and reading the knowledge matching base of the file by adopting different display modes.
Preferably, the fields of the knowledge matching base include a description in the field, written description, specific meaning and content interpretation, provenance, content description.
Preferably, in the step S2, the type of the uploaded file is analyzed and judged, and if the file is PDF, PPT, PPTX, DOC, DOCX, XLS, XLXS, CAD, true, DLF, the file is converted into an OFD file; if the file is a picture or a scanned file, performing OCR on the file to generate a double-layer OFD file; if the file is an audio file, a video file and the like, the file is used as a resource to be filled into a frame of the OFD, characters in the file are identified, and the file is used as a subtitle of the audio and video to be synchronously displayed.
Preferably, the types of the fields to which the documents belong include medical industry, scientific industry, educational industry, politics and chemistry; the general data refers to: industry interpretation information is the same between different domains.
Preferably, the specific steps of analyzing the file in step S4 are:
step S41: analyzing file content information, and carrying out semantic analysis on phrases, entries and related sentences;
step S42: obtaining a text queue to be expanded;
Step S43: inputting the text queues into a knowledge model to obtain key and value models corresponding to each other one by one;
Step S44: the extended text generated in step S43 is saved to generate a new OFD file.
Preferably, the expanded text is an association relationship between the content for recording the original text and the explanation of the original text.
Preferably, the specific steps for reading by using the OFD reader in the step S5 are as follows:
Step S51, loading OFD original text basic content by using an OFD reader, and judging whether an expansion file exists in the original text;
step S52: if the original text has the expansion file, analyzing the expansion file, and displaying the identification of the specified content of the original text, wherein the specified content comprises words, entries and sentences of the original text;
Step S53: the content in the extension file is displayed in an OFD original document in various forms, wherein the display forms comprise mouse suspension display, and annotation content description is carried out on the right side of the OFD original document;
Step S54: the drawing menu shows the names and interpretations contained throughout the text in the text.
Preferably, the content operation in the knowledge matching base comprises editing, modifying and erasing; and updating and adjusting the content of the expansion file displayed by the OFD original text in real time according to the updating of the knowledge matching base.
Preferably, during reading, different modes can be selected to control whether the display content is dynamically displayed or hidden.
Preferably, when the original OFD file is a combined file, the content information of whether hidden knowledge exists can be displayed on the combined file directory.
Compared with the prior art, the invention has the beneficial effects that:
(1) The method effectively fuses the AI technology and the OFD expansion file, creates a method for hiding the knowledge in the file, and processes the file by the technology so that a large amount of knowledge content is attached to the original file, thereby improving the reading experience of readers and improving the reading efficiency;
(2) The invention can convert various files through the OFD conversion technology, can expand the range of hiding knowledge in the files, and is suitable for more file types;
(3) The invention supports offline reading, and the files can attach knowledge to the files after processing, and other online knowledge bases or any background support are not needed.
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FIG. 1 is a flow chart of the present invention;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1, the present invention provides a method for hiding knowledge from text files by AI technology for independent or combined reading, comprising the following steps:
Step S1: setting a knowledge matching base, wherein the fields of the knowledge matching base comprise the description of the field and the writing, the specific meaning and the explanation, provenance and description of the content, and a series of operations can be performed on the content in the knowledge matching base, and the content can be edited, modified and erased;
Step S2: when uploading a file, uploading the file to a server, analyzing and judging the type of the uploaded file, if the type of the file is not a standard OFD file, converting the file into the standard OFD file, and when analyzing and judging the type of the uploaded file, converting the file into the OFD file if the type of the uploaded file is PDF, PPT, PPTX, DOC, DOCX, XLS, XLXS, CAD, true, DLF files, wherein the DLF file is a compressed package file, the DLF file internally comprises a guide file and a plurality of OFD files, and the guide file mainly records the association relation among the files, the entry of the file, the storage path of the OFD file, the triggering position and the skip event between the OFD and the OFD; if the file is a picture, for example PNG, JPG, TIF or a scanned file, performing OCR on the file to generate a double-layer OFD file; if the file is an audio file, a video file and the like, filling the file into a frame of the OFD as a resource, identifying characters in the file, and synchronously displaying the file as subtitles of the audio and video;
Step S3: analyzing the file by using the NLP to acquire the field type of the file, and matching the universal data in the knowledge matching base if the field type of the file cannot be judged, wherein the field type of the file comprises industries such as medical industry, scientific industry, education industry, politics, chemistry, agriculture and the like; the general data refers to: industry interpretation information that is the same between different domains;
Step S4: according to the type of the file field, analyzing and acquiring file content information to obtain a text queue to be expanded, inputting the queue into a knowledge model, and acquiring a key and value key value pair model in one-to-one correspondence, wherein the key refers to the content of an original text, the value refers to the explanation of the original text, and the specific steps of analyzing the file content information are as follows:
step S41: analyzing the content information of the file, and carrying out semantic analysis on phrases, entries and related sentences in the file;
step S42: obtaining a text queue to be expanded, wherein the expanded text queue refers to a list of original text contents;
Step S43: inputting the text queue, namely the list of the original text contents, into a knowledge model, and obtaining a key and value model corresponding to the corresponding interpretation original text contents one by one through original text retrieval and matching, so as to generate an expanded text;
Step S44: directly writing the generated expanded text, namely a text queue for recording the association relation between the content of the original text and the explanation of the original text, into an OFD file, thereby saving and generating a new OFD file;
Step S5: recording association relation information between the content (key) of the original text and the explanation (value) of the original text, typesetting according to a format to form a knowledge base xml file, generating an OFD expansion file package, generating a new OFD file according to the OFD expansion file package, and carrying out real-time updating and adjustment on the expansion file content displayed by the OFD original text according to the updating of a knowledge matching base, wherein the specific steps of reading by adopting an OFD reader are as follows:
step S51, loading and generating new OFD original text basic content by using an OFD reader, and judging whether an expansion file package of a 'knowledge matching base' exists in the original text if the OFD file is an independent file;
step S52: if the original text has the expansion file package, analyzing the expansion file package, and displaying the identification of the specified content of the original text, wherein the specified content comprises words, entries and sentences of the original text;
Step S53: the content in the extension file is displayed in an OFD original document in various forms, wherein the display forms comprise mouse suspension display, annotation content description on the right side of the OFD original document and the like;
Step S54: drawing a menu in an original text to show names and explanations contained in the whole text;
step S6: when reading, the original content of the OFD file is loaded by the OFD reader, then whether an expansion file package of the knowledge matching library exists is judged, if the original file exists, the expansion file of the knowledge matching library indicates that the OFD file already has knowledge hiding, the expansion file package of the knowledge matching library is analyzed, the appointed content in the original file such as words, terms and sentences is displayed, and the knowledge matching library of the file is displayed and read by adopting different display modes, such as mouse suspension display, content description of annotation state on the right side and unified display of all involved terms, so that whether the displayed content is dynamically displayed or hidden can be controlled.
When the original OFD file is a combined file, judging whether an extended file package of a knowledge matching library exists in the combined file when the combined file is read, if the extended file package of the knowledge matching library exists in the file, analyzing the extended file package of the knowledge matching library in the combined file, wherein the extended files of the combined file are all stored in respective file contents, the contents existing in the extended files of the knowledge matching library can be displayed in the OFD file in one or more modes of mouse suspension display, right side annotation state content description and unified display of all related terms, and appointed contents in the OFD file can be marked and displayed, a reader can dynamically control whether the knowledge is displayed or hidden, and meanwhile, the content information of the hidden knowledge can be displayed on the directory of the combined file, so that the AI technology and the OFD extended file can be effectively fused, a method for hiding the knowledge in the file is created, a great amount of knowledge contents can be attached to the original file through the processing of the original file, the reader experience is improved, and the reader reading efficiency is improved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims (10)

1.基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于，包括以下步骤：1. A method for hiding knowledge in text files for independent or combined reading based on AI technology, characterized by comprising the following steps: 步骤S1：设置知识匹配库;Step S1: Setting the knowledge matching library; 步骤S2：分析判断上传的文件类型，若文件类型不为标准的OFD文件，则转换为标准的OFD文件；Step S2: Analyze and determine the type of the uploaded file. If the file type is not a standard OFD file, convert it to a standard OFD file. 步骤S3：利用NLP对文件进行分析，获取文件所属领域类型，若不能判断文件的领域类型，则匹配知识匹配库中的通用数据；Step S3: Analyze the file using NLP to obtain the field type to which the file belongs. If the field type of the file cannot be determined, match the general data in the knowledge matching library; 步骤S4：根据文件领域类型，解析并获取文件内容信息，得到需要扩展的文本队列，将文本队列输入到知识模型中，获取到一一对应的 key、value键值对模型；Step S4: According to the file domain type, parse and obtain the file content information, obtain the text queue that needs to be expanded, input the text queue into the knowledge model, and obtain a one-to-one corresponding key, value key-value pair model; 步骤S5：记录原文的内容以及原文的解释说明之间的关联关系信息按照格式进行排版，形成知识库xml文件，生成OFD的拓展文件包，生成新的OFD文件，新的OFD文件用于在线或离线传输并阅读；Step S5: Record the content of the original text and the information on the relationship between the explanations of the original text and format them according to the format to form a knowledge base xml file, generate an extended file package of OFD, and generate a new OFD file. The new OFD file is used for online or offline transmission and reading; 步骤S6：利用OFD阅读器加载OFD文件的原文件进行阅读，若原文件存在知识拓展文件包，则解析知识拓展文件包，并将原文文件指定的内容标识显示，并采用不同的显示模式对文件的知识匹配库进行展示阅读。Step S6: Use the OFD reader to load the original OFD file for reading. If the original file contains a knowledge extension file package, parse the knowledge extension file package, display the content identifier specified by the original file, and use different display modes to display and read the knowledge matching library of the file. 2.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：所述知识匹配库的字段包括所属领域、书面的描述、具体的含义与内容解释、出处、内容描述。2. According to the method of hiding knowledge in text files for independent or combined reading based on AI technology as described in claim 1, it is characterized in that the fields of the knowledge matching library include the field to which it belongs, written description, specific meaning and content explanation, source, and content description. 3.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：所述步骤S2中分析判断上传的文件类型，如果是PDF、PPT、PPTX、DOC、DOCX、XLS、XLXS、CAD、True、DLF文件时，将其转换为OFD文件；如果是图片或者扫描件文件时，将文件进行OCR生成双层的OFD文件；如果是音频、视频文件，则将其作为资源填充到OFD的框架中，并将其中的文字识别出来，作为音视频的字幕同步进行展示。3. According to the method of hiding knowledge in text files for independent or combined reading based on AI technology as described in claim 1, it is characterized in that: in the step S2, the uploaded file type is analyzed and determined, and if it is a PDF, PPT, PPTX, DOC, DOCX, XLS, XLXS, CAD, True, DLF file, it is converted into an OFD file; if it is a picture or scanned file, the file is subjected to OCR to generate a double-layer OFD file; if it is an audio or video file, it is filled into the OFD framework as a resource, and the text therein is recognized and displayed synchronously as subtitles of audio and video. 4.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：所述文件所属领域类型包括医疗行业、科技行业、教育行业、政法、化学；所述通用数据是指：不同领域之间相同的行业解释信息。4. According to the method of hiding knowledge in text files for independent or combined reading based on AI technology as described in claim 1, it is characterized in that: the field types to which the files belong include medical industry, science and technology industry, education industry, politics and law, and chemistry; the common data refers to: the same industry explanation information between different fields. 5.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于，所述步骤S4中分析文件的具体步骤为：5. The method for hiding knowledge in text files based on AI technology and reading them independently or in combination according to claim 1, characterized in that the specific steps of analyzing the files in step S4 are: 步骤S41：解析文件内容信息，对词组，词条、相关语句进行语义分析；Step S41: parsing the file content information, and performing semantic analysis on phrases, entries, and related sentences; 步骤S42：获得需要进行扩展的文本队列；Step S42: obtaining a text queue that needs to be expanded; 步骤S43：将上述文本队列输入到知识模型中，获取到一一对应的key、value模型；Step S43: input the above text queue into the knowledge model to obtain a one-to-one corresponding key and value model; 步骤S44：将步骤S43中生成的扩展文本保存生成新的OFD文件。Step S44: Save the extended text generated in step S43 to generate a new OFD file. 6.根据权利要求5所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：所述步骤S44中扩展文本为用于记录原文的内容以及原文的解释说明之间的关联关系。6. The method for hiding knowledge in text files for independent or combined reading based on AI technology according to claim 5 is characterized in that the expanded text in step S44 is used to record the relationship between the content of the original text and the explanation of the original text. 7.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于，所述步骤S5中采用OFD阅读器进行阅读的具体步骤如下：7. The method for hiding knowledge in text files based on AI technology and reading them independently or in combination according to claim 1, characterized in that the specific steps of using the OFD reader to read in step S5 are as follows: 步骤S51:利用OFD阅读器加载OFD原文基本内容，并判断原文是否存在拓展文件包；Step S51: Use the OFD reader to load the basic content of the OFD original text, and determine whether there is an extended file package in the original text; 步骤S52：若原文存在拓展文件包，则解析拓展文件包，并将原文中指定内容进行标识显示，指定内容包括原文的单词，词条，语句；Step S52: if the original text contains an extended file package, the extended file package is parsed, and the designated content in the original text is marked and displayed, and the designated content includes words, terms, and sentences in the original text; 步骤S53：并将拓展文件包中内容以多种形式展示在OFD原文中，展现形式包括鼠标悬浮展示，OFD原文右侧批注内容描述；Step S53: Display the content in the extended file package in the OFD original text in various forms, including mouse hover display and annotation content description on the right side of the OFD original text; 步骤S54：在原文中绘制菜单展示全文中包含的名字及解释。Step S54: Draw a menu in the original text to display the names and explanations contained in the full text. 8.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：对知识匹配库中的内容操作包括编辑、修改、擦除；OFD原文展现的拓展文件内容根据知识匹配库的更新进行实时更新调整。8. According to the method of hiding knowledge in text files for independent or combined reading based on AI technology as described in claim 1, it is characterized in that: the content operations in the knowledge matching library include editing, modifying, and erasing; the extended file content displayed by the OFD original text is updated and adjusted in real time according to the update of the knowledge matching library. 9.根据权利要求7所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：在阅读过程中，能够选择不同模式，控制展示内容是否动态显示或隐藏。9. The method for hiding knowledge in text files based on AI technology for independent or combined reading according to claim 7 is characterized in that: during the reading process, different modes can be selected to control whether the displayed content is dynamically displayed or hidden. 10.根据权利要求1所述的基于AI技术将知识隐藏于文本文件独立或组合阅读的方法，其特征在于：当原文OFD文件是组合文件时，组合文件目录上能够展示是否存在隐藏知识的内容信息。10. The method for hiding knowledge in text files for independent or combined reading based on AI technology according to claim 1 is characterized in that: when the original OFD file is a combined file, the combined file directory can display content information on whether there is hidden knowledge.
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