Text design method fusing semantic assistance and visual design

Abstract

The invention discloses a text design method fusing semantic assistance and visual design. According to the technical scheme, the method comprises the steps of 1, text obtaining; step 2, text processing; step 3, text display; the reading efficiency can be improved, and key information can be quickly obtained; through accurate typesetting of the text and effective integration of the knowledge points, a reader can quickly distinguish different parts such as the text, word interpretation and knowledge point summarization, and quickly position key information. For example, when an academic paper is read, a reader can see the introduction, the core viewpoint and the explanation of the terminology of an author at a glance, and does not need to strenuously search in a large number of characters. According to the method, reading disorder can be reduced, uncommon characters in the text can be labeled with phonetic symbols, complex words and terminologies can be explained in detail, and reading difficulty of readers due to character and word disorder is reduced. According to the invention, understanding of contents is deepened.

Description

Technical Field

[0001] The present invention belongs to the technical field of word processing, and more specifically, particularly relates to a text design method integrating semantic assistance and visual design. Background Art

[0002] The field of text processing technology specifically covers multiple sub-fields such as text design, typesetting and layout, and visual presentation. In terms of text design, it involves structural planning of text content, semantic interpretation assistance (such as word explanation and knowledge point summary), etc.; the typesetting and layout field includes factors that affect the reading experience, such as the arrangement of text, paragraph spacing, and font selection; the visual presentation field focuses on the appearance of the text, including color matching, graphic element application, and interface style design, especially combining appearance design with technical means to achieve a better reading experience.

[0003] In the modern reading environment, whether it is an e-book, online article or learning material, the layout of the text is crucial to the reading experience. However, current typesetting technology has many limitations. Taking learning apps as an example, when presenting the content of the text, the layout of word explanations, knowledge point summaries and other parts often lacks differentiation. The word explanation may simply follow the word without highlighting it, which makes it easy for students to overlook it when browsing quickly. The knowledge point summary may be mixed with the text, and the key points are not highlighted through reasonable typesetting methods (such as using different fonts, font sizes or adding separators, etc.), which affects readers' acquisition of key information.

[0004] In some electronic document reading software, the layout of documents containing multiple languages ​​or rare characters in ancient documents is not well handled. The font sizes and fonts of different languages ​​may not be coordinated, and the display of rare characters may not take into account the reader's need to check the pronunciation and explanation. There is a lack of phonetic symbols and quick explanation entrances, which makes reading difficult.

[0005] One of the current development directions is visual design. With the development of multimedia technology, readers expect that the text design can make better use of visual elements to assist understanding. However, there are obvious deficiencies in this regard. For example, in electronic dictionary applications, although there are text descriptions for the explanation of words, there is a lack of intuitive graphics or images to assist in understanding some abstract concepts. In literary reading applications, if the author's profile can be integrated with the author's photo or pictures of related works, it will be more helpful for readers to understand the author, but most applications simply list the author's life in text, which lacks visual appeal.

[0006] On some online learning platforms, there is almost no visualization of abstract content such as thoughts and feelings. If the thoughts and feelings of the article can be expressed through color matching and simple charts, it will be more helpful for readers to grasp the main idea of ​​the article, but existing designs often ignore this point.

[0007] Another current development direction is information interaction. Although information interaction is not the focus of this technology, existing reading technologies also have some problems related to text design in this regard. Taking traditional paper books as an example, when readers encounter words or knowledge points that they do not understand during reading, they cannot directly obtain relevant explanations and need to rely on external reference books, which increases the inconvenience of reading. In terms of electronic reading, although some applications provide some interactive functions, these functions may not be closely integrated with the text design. For example, the pop-up explanation window may not be consistent with the layout and style of the text, affecting the reading experience. At the same time, for some special text content, such as the pronunciation and interpretation of words in classical literature, existing electronic reading applications may not have targeted display designs and cannot meet readers' needs for accurate acquisition of such information. Summary of the invention

[0008] In view of the problems existing in the prior art, the purpose of the present invention is to provide a text design method integrating semantic assistance and visual design.

[0009] To achieve the above object, the present invention provides the following technical solution: a text design method integrating semantic assistance and visual design, comprising the following steps: Step 1, text acquisition: the front-end interface module determines that the connection with the back-end database module adopts the https protocol for communication. The front-end interface module constructs an https request message according to the pre-set rules. The request message contains relevant parameters for obtaining the text content; the front-end interface module sends the constructed https request to the back-end database module. After receiving the https request, the back-end database module first verifies the request; if the request verification passes, the back-end database module searches the database according to the parameters in the request, traverses the relevant table structure storing the text data, and quickly locates the text records that meet the conditions through the index and query algorithm; the back-end database module extracts the text content that meets the conditions and performs necessary processing on it; the back-end database module encapsulates the processed text content in the response message through the https protocol and sends it back to the front-end interface module; the front-end interface module receives the response message sent by the back-end database module, first verifies the legitimacy and integrity of the response, if the verification passes, extracts the text content in the response message, and performs preliminary format verification on it to ensure that the text content meets the expected format requirements; then the obtained and verified text content is transmitted to the front-end interface module itself for subsequent processing; Step 2: Text processing: The front-end interface module processes the input text content. First, it adds phonetic symbols to specific words in the text. Then, it generates explanation content for the words that need to be explained in the text, and obtains detailed explanations of the words by querying the internal word explanation database and using network resources. Finally, it integrates and summarizes the knowledge points in the text. By analyzing the content of the text, it extracts information such as the author's profile and the thoughts and feelings of the article, and integrates this knowledge into the text in a reasonable way. The processed text content is transmitted to the display module for display; Step 3, text display: The display module receives the processed text content transmitted by the front-end interface module, and converts the text content into a visible image signal according to the preset display format, including font, font size, color and typesetting rules, and displays it on a screen with a white background color, presenting the designed text content to the user.

[0010] Preferably, in step 1, the front-end interface module constructs an https request message according to preset rules, and the relevant parameters for obtaining the text content contained in the request message include: a unique identifier of the text, a category or specific author information, so as to clearly specify the text content to be obtained.

[0011] Preferably, in the step 1, after receiving the https request, the backend database module first verifies the request, including verifying the legitimacy of the source of the request and the validity of the request parameters.

[0012] Preferably, in step 1, the back-end database module extracts the text content that meets the conditions and performs necessary processing on it, including decrypting or removing irrelevant tag information, to ensure the accuracy and availability of the text content.

[0013] Preferably, in step 2, firstly, phonetic symbols are added to specific words in the text, and the accuracy of the phonetic symbol annotation is ensured by querying the internal pronunciation database and the phonetic symbol annotation algorithm.

[0014] Preferably, in step 2, a detailed explanation of the word is obtained by querying an internal word explanation database and utilizing network resources. Different explanation presentation methods are used for different types of words. For common words, explanations are given in concise text below the words. For professional terms or complex words, a special explanation window is set next to or below the main text to display the explanation content in detail, and the explanation content includes definitions, examples, and related concepts.

[0015] Preferably, the back-end database module stores various text data and related auxiliary data, including a pronunciation database and a word explanation database, and effectively manages and maintains the data. The management and maintenance means include data storage, retrieval, and update operations; the back-end database module uses a MySQL database to store data, and improves data retrieval efficiency by defining appropriate table structures and indexes; for the text data, a table is created containing text content, author information, and article classification fields; for the pronunciation database, a table is created containing Chinese characters, pinyin, and other fields.

[0016] Preferably, the front-end interface module extracts the main text content from the back-end database module through an interface, and performs preliminary processing on the extracted text, including adding phonetic symbols, generating explanations, and integrating knowledge operations to meet the requirements of the text design; the front-end interface module uses interface technology to communicate with the back-end database module to obtain the main text content; then, the main text content is processed using algorithms and rules. For the addition of phonetic symbols, phonetic symbols are added to specific words by querying the internal pronunciation database and phonetic symbol annotation algorithm; for the generation of explanations, explanation content is generated for the words that need to be explained through the internal word explanation database, and different explanation presentation methods are used according to the word type; for knowledge integration, the author's profile and the article's ideological and emotional information are extracted through analysis of the main text content, and this knowledge is integrated into the main text in a reasonable manner.

[0017] Technical effects and advantages of the present invention: The present invention can improve reading efficiency and quickly obtain key information; through the precise typesetting of the text and the effective integration of knowledge points, readers can quickly distinguish different parts such as the text, word explanation, knowledge point summary, etc., and quickly locate key information. For example, when reading an academic paper, the reader can see the author's profile, core ideas, and explanations of professional terms at a glance, without having to search laboriously in a large amount of text. The present invention can reduce reading difficulties, annotate uncommon characters in the text with phonetic symbols, and provide detailed explanations for complex words and professional terms, thereby reducing the reading difficulties caused by word barriers for readers. This enables readers to understand the content more smoothly when reading ancient documents, professional books, or foreign language translations. The present invention can enhance the reading experience and enhance visual appeal. Although the present technical solution does not use graphics or images, it can still enhance the visual appeal of the text through unique typesetting design and color matching. For example, according to the theme and emotional tendency of the article, select appropriate fonts and colors to make the text more beautiful and appealing, attract readers' attention, and increase reading interest. The present invention deepens the understanding of the content. By effectively presenting the author's profile and the thoughts and feelings of the article, readers can better understand the creative background and core theme of the text. At the same time, the reasonable layout and presentation of word explanations also help readers grasp the meaning of words more accurately, thereby deepening their understanding of the entire text content. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart provided by the present invention.

[0019] Figure 2 It is a schematic diagram of an implementation method provided by the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] like Figure 1-Figure 2 As shown, an embodiment of the present invention provides a text design method that integrates semantic assistance and visual design, and the structure and functional principles used are as follows: the structure used in this method mainly includes a back-end database module, a front-end interface module and a display module.

[0022] Among them, the back-end database module is responsible for storing various text data and related auxiliary data (such as pronunciation database, word explanation database, etc.); it can effectively manage and maintain data, including data storage, retrieval, update and other operations.

[0023] Principle of the back-end interface module: Use MySQL database to store data. Improve data retrieval efficiency by defining appropriate table structures and indexes. For example, for text data, you can create a table containing fields such as text content, author information, and article classification; for a phonetic database, you can create a table containing fields such as Chinese characters and pinyin.

[0024] Among them, the front-end interface module has the following functions: extracting the text content from the back-end database module through the interface, and performing preliminary processing on the extracted text, including adding phonetic symbols, generating explanations, integrating knowledge, etc., to meet the requirements of text design.

[0025] Principle of the front-end interface module: Use the corresponding interface technology to communicate with the back-end database module to obtain the text content. Then, use a series of algorithms and rules to process the text content. For adding phonetic symbols, add phonetic symbols to specific words by querying the internal pronunciation database and phonetic symbol annotation algorithm; for explanation generation, generate explanation content for the words that need to be explained through the internal word explanation database, and use different explanation presentation methods according to the word type; for knowledge integration, extract information such as the author's profile and the thoughts and feelings of the article through the analysis of the text content, and integrate this knowledge into the text in a reasonable way.

[0026] The steps are described in detail below: The first is the text acquisition step: the front-end interface module determines that the connection with the back-end database module uses the https protocol for communication. The front-end interface module constructs an https request message according to the pre-set rules. The request message contains relevant parameters for obtaining the text content, such as the unique identifier of the text, the category to which it belongs, or specific author information, so as to clarify the text content to be obtained. The front-end interface module sends the constructed https request to the back-end database module. After receiving the https request, the back-end database module first verifies the request, including verifying the legitimacy of the source of the request and the validity of the request parameters. If the request verification passes, the back-end database module searches the database according to the parameters in the request. It traverses the relevant table structure storing the text data and quickly locates the text records that meet the conditions through indexing and query algorithms. The back-end database module extracts the text content that meets the conditions and performs necessary processing on it, such as decryption (if the text data is encrypted and stored) or removing irrelevant tag information to ensure the accuracy and availability of the text content. The back-end database module encapsulates the processed text content in the response message through the https protocol and sends it back to the front-end interface module. The front-end interface module receives the response message sent by the back-end database module and first verifies the legitimacy and integrity of the response. If the verification is successful, the body content in the response message is extracted and a preliminary format verification is performed on it to ensure that the body content meets the expected format requirements. The obtained and verified body content is transmitted to the front-end interface module itself for subsequent processing.

[0027] The second is the text processing step: the front-end interface module processes the input text content. First, add phonetic symbols to specific words in the text. Ensure the accuracy of phonetic symbol annotation by querying the internal word pronunciation database and phonetic symbol annotation algorithm. Secondly, generate explanation content for the words that need to be explained in the text. Obtain detailed explanations of words by querying the internal word explanation database and using network resources. Different explanation presentation methods are used for different types of words. For common words, explanations are given in concise text below the words; for professional terms or complex words, a special explanation window is set next to or below the text to display the explanation content in detail, including definitions, examples, related concepts, etc., to help readers better understand. Finally, integrate and summarize the knowledge points of the text. By analyzing the content of the text, extract information such as the author's profile and the thoughts and feelings of the article, and integrate this knowledge into the text in a reasonable way. The processed text content is transmitted to the display module for display.

[0028] The last step is the text display step: the display module receives the processed text content transmitted by the front-end interface module. According to the preset display format (such as font, font size, color, etc.) and typesetting rules, the text content is converted into a visible image signal and displayed on a screen with a white background color, presenting the designed text content to the user.

[0029] like Figure 1-Figure 2 As shown, in general, the technical effects of the present invention are as follows: the present invention can improve reading efficiency and quickly obtain key information; through the precise typesetting of the text and the effective integration of knowledge points, readers can quickly distinguish different parts such as the text, word explanation, knowledge point summary, etc., and quickly locate key information. For example, when reading an academic paper, the reader can see the author's profile, core ideas and explanations of professional terms at a glance, without having to search laboriously in a large amount of text. The present invention can reduce reading difficulties, annotate uncommon characters in the text with phonetic symbols, and provide detailed explanations for complex words and professional terms, thereby reducing the reading difficulties caused by word barriers for readers. This enables readers to understand the content more smoothly when reading ancient documents, professional books or foreign translation works. The present invention can enhance the reading experience and enhance visual appeal. Although the present technical solution does not use graphics or images, it can still enhance the visual appeal of the text through unique typesetting design and color matching. For example, according to the theme and emotional tendency of the article, select appropriate fonts and colors to make the text more beautiful and appealing, attract readers' attention, and improve reading interest. The present invention deepens the understanding of the content. By effectively presenting the author's profile and the thoughts and feelings of the article, readers can better understand the creative background and core theme of the text. At the same time, the reasonable layout and presentation of word explanations also help readers grasp the meaning of words more accurately, thereby deepening their understanding of the entire text content.

[0030] The structural composition and functional connection relationship of the present invention are as follows: Content recognition module, function: to recognize and analyze the existing text content. Including identifying the structural level of the text, such as paragraphs, chapters, etc.; judging the type of the text, such as literary works, academic papers, etc.; extracting key information of the text, such as the theme, core concepts, etc. At the same time, according to the type and characteristics of the text, preliminarily determine the typesetting format of the text, such as font, font size, line spacing, etc., to ensure basic readability. Connection relationship: provide the analyzed text data for the phonetic symbol adding module, interpretation generation module and knowledge integration module.

[0031] Phonetic symbol adding module, function: generate explanation content for words that need to be explained in the text. Obtain detailed explanations of words by querying the internal word explanation database. Different explanation presentation methods are used for different types of words. For common words, explanations are given in concise text below the words; for professional terms or complex words, a special explanation window is set up next to or below the text to display the explanation content in detail, including definitions, examples, related concepts, etc., to help readers better understand. Connection relationship: Receive the data provided by the phonetic symbol adding module, and pass the text data containing word explanations to the knowledge integration module.

[0032] Explanation generation module, function: generate explanation content for words that need to be explained in the text. Obtain detailed explanations of words by querying the internal word explanation database and using network resources. Different explanation presentation methods are used for different types of words. For common words, explanations are given in concise text below the words; for professional terms or complex words, a special explanation window is set next to or below the text to display the explanation content in detail, including definitions, examples, related concepts, etc., to help readers better understand. Connection relationship: Receive the data provided by the phonetic symbol addition module, and pass the text data containing word explanations to the knowledge integration module.

[0033] Knowledge integration module, function: to integrate and summarize the knowledge points of the text. This includes extracting the author's profile, obtaining relevant information about the author, such as life experience, creative background, etc., through analyzing the content of the text; sorting out the thoughts and feelings of the article, and determining the core emotions and values ​​conveyed by the article through analyzing the emotional tendency of the text. Then, the integrated knowledge is integrated into the text in a reasonable way. For example, a special knowledge display area is set at the beginning or end of the text, or knowledge prompt information is inserted near relevant paragraphs of the text, so that readers can easily obtain this knowledge during the reading process and enhance their understanding of the text. Connection relationship: Receive the data provided by the interpretation generation module, complete the final text design integration, and output the complete text design results.

[0034] Working principle of the content recognition module: Identify the structural hierarchy of the existing text body, determine the type of the text body, extract key information, and preliminarily determine the layout format. For example, for a literary work, identify the paragraph structure, determine it as a lyrical work, extract the theme as "love", and preliminarily determine the layout format of using Song typeface, 10.5-point font size, and 1.5-line spacing. Transmit the analyzed and processed text body data to the phonetic symbol adding module, the explanation generating module, and the knowledge integration module.

[0035] Working principle of the phonetic symbol adding module: Receive the data provided by the content recognition module and add phonetic symbols to specific words in the text body. For example, for the word "taotie", add the phonetic symbols "tāotiè" by querying the phonetic database and the phonetic symbol annotation algorithm. Transmit the text body data with added phonetic symbols to the explanation generating module and the knowledge integration module.

[0036] Working principle of the explanation generating module: Receive the data provided by the phonetic symbol adding module and explain the words that need to be explained in the text body. For common words, such as "happy", give the explanation "feeling happy or satisfied" below the word; for technical terms, such as "quantum mechanics", set up a special explanation window beside or below the text body to display the definition, examples, related concepts, etc. in detail. Transmit the text body data containing word explanations to the knowledge integration module.

[0037] Working principle of the knowledge integration module: Receive the data provided by the explanation generating module, integrate and summarize the knowledge points of the text body. For example, for a work about a certain writer, extract the author's profile including life experiences, creative background, etc., and sort out the ideological feelings of the article such as the core emotions and values conveyed. Integrate the integrated knowledge into the text body in a reasonable way. For example, set up a special knowledge display area at the beginning of the text body and write the content such as the author's profile and the ideological feelings of the article at the beginning of the text body. Output the final text body design result.

[0038] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A text design method integrating semantic assistance and visual design, characterized in that: The following steps are involved: Step 1, text acquisition: the front-end interface module determines that the connection with the back-end database module adopts the https protocol for communication. The front-end interface module constructs an https request message according to the pre-set rules. The request message contains relevant parameters for obtaining the text content; the front-end interface module sends the constructed https request to the back-end database module. After receiving the https request, the back-end database module first verifies the request; if the request verification passes, the back-end database module searches the database according to the parameters in the request, traverses the relevant table structure storing the text data, and quickly locates the text records that meet the conditions through the index and query algorithm; the back-end database module extracts the text content that meets the conditions and performs necessary processing on it; the back-end database module encapsulates the processed text content in the response message through the https protocol and sends it back to the front-end interface module; the front-end interface module receives the response message sent by the back-end database module, first verifies the legitimacy and integrity of the response, if the verification passes, extracts the text content in the response message, and performs preliminary format verification on it to ensure that the text content meets the expected format requirements; then the obtained and verified text content is transmitted to the front-end interface module itself for subsequent processing; Step 2: Text processing: The front-end interface module processes the input text content, first adding phonetic symbols to specific words in the text; Then, the explanation content is generated for the words that need to be explained in the text, and the detailed explanation of the words is obtained by querying the internal word explanation database and using network resources; finally, the knowledge points of the text are integrated and summarized, and the information such as the author's profile and the thoughts and feelings of the article are extracted through the analysis of the text content, and this knowledge is integrated into the text in a reasonable way, and the processed text content is transmitted to the display module for display; Step 3, text display: The display module receives the processed text content transmitted by the front-end interface module, and converts the text content into a visible image signal according to the preset display format, including font, font size, color and typesetting rules, and displays it on a screen with a white background color, presenting the designed text content to the user.

2. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: In the step 1, the front-end interface module constructs an https request message according to a preset rule. The relevant parameters for obtaining the text content contained in the request message include: the unique identifier of the text, the category to which it belongs or the specific author information, so as to clearly specify the text content to be obtained.

3. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: In the step 1, after receiving the https request, the backend database module first verifies the request, including verifying the legitimacy of the source of the request and the validity of the request parameters.

4. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: In the step 1, the back-end database module extracts the text content that meets the conditions and performs necessary processing on it, including decrypting or removing irrelevant tag information, to ensure the accuracy and availability of the text content.

5. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: In the step 2, firstly, phonetic symbols are added to specific words in the text, and the accuracy of the phonetic symbol annotation is ensured by querying the internal pronunciation database and the phonetic symbol annotation algorithm.

6. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: In the step 2, by querying the internal word explanation database and using network resources, a detailed explanation of the word is obtained. Different explanation presentation methods are used for different types of words. For common words, explanations are given in concise text below the words. For professional terms or complex words, a special explanation window is set up next to or below the main text to display the explanation content in detail, including definitions, examples, and related concepts.

7. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: The back-end database module stores various text data and related auxiliary data, including a pronunciation database and a word explanation database, and effectively manages and maintains the data. The management and maintenance means include data storage, retrieval, and update operations; the back-end database module uses a MySQL database to store data, and improves data retrieval efficiency by defining appropriate table structures and indexes; for the text data, a table is created that includes text content, author information, and article classification fields; for the pronunciation database, a table is created that includes Chinese characters, pinyin, and other fields.

8. The text design method integrating semantic assistance and visual design according to claim 1, characterized in that: The front-end interface module extracts the text content from the back-end database module through the interface, and performs preliminary processing on the extracted text, including adding phonetic symbols, generating explanations, and integrating knowledge operations to meet the requirements of text design; the front-end interface module uses the interface technology to communicate with the back-end database module to obtain the text content; then, the text content is processed using algorithms and rules, and for adding phonetic symbols, phonetic symbols are added to specific words by querying the internal character pronunciation database and phonetic symbol annotation algorithm; For explanation generation, the internal word explanation database is used to generate explanation content for the words that need to be explained, and different explanation presentation methods are used according to the word type; For knowledge integration, by analyzing the content of the text, we extract the author's profile and the article's thoughts and feelings, and integrate this knowledge into the text in a reasonable way.

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