A method for disseminating and pushing digital publication content

Abstract

The present application relates to the field of content push, and in particular to a method for disseminating and pushing digital publication content. The method includes: analyzing several digital publications on grain and oil quality inspection to determine several publication information; analyzing user information to determine the push target factory, determining production information based on the push target factory, and determining historical information of several similar factories based on the production information; determining difference information based on several publication information and historical information, and determining historical viewing information related to the difference information based on the difference information; analyzing historical viewing information to determine the viewing content and user acceptance of several similar factories; determining and pushing the push plan of the push target factory based on the viewing content, production information, user acceptance and several publication information. The present application determines the regionality and timeliness of publications by analyzing publications, determines the push target based on user information, and optimizes the push plan in combination with the history of similar factories to improve user acceptance and user satisfaction.

Description

Technical Field

[0001] The present application relates to the field of content push, and in particular to a method for disseminating and pushing digital publication content. Background Art

[0002] Existing technologies for the dissemination and push of digital publishing content cover cross-platform reading, digital copyright protection, personalized recommendations, social media dissemination, cloud computing and big data applications, which improve user experience, expand the scope of dissemination, and promote the dissemination of content.

[0003] At present, the dissemination and push of digital publications on grain and oil quality inspection lacks personalized recommendations, making it difficult to predict users' specific needs and update push content in a timely manner. User acceptance is low, and content push efficiency is low. Summary of the invention

[0004] The present application provides a method for disseminating and pushing digital publication content to solve the above-mentioned problems.

[0005] In a first aspect, the present application provides a method for disseminating and pushing digital publication content, the method comprising: Obtain and analyze several digital publications on grain and oil quality testing and determine some publication information; Acquire and analyze user information, determine a push target factory, determine production information based on the push target factory, and determine historical information of several similar factories based on the production information; Determine difference information according to the plurality of publication information and the historical information, and determine historical viewing information related to the difference information according to the difference information; Analyze the historical viewing information to determine viewing content and user acceptance of the several similar factories; According to the viewing content, the production information, the user acceptance and the information of the plurality of publications, a push plan for the push target factory is determined and pushed.

[0006] The solution provided by this application determines the target factory for push by analyzing user information and factory production information, ensuring that the pushed content matches the actual needs and concerns of the factory. Combined with the historical information of similar factories, the pushed content is further refined to make it closer to the actual application scenarios of the target factory. Analyze the historical viewing information and user acceptance of similar factories to understand which types of content similar factories are more interested in, so as to optimize the push plan, improve the user acceptance of the target factory, and make the pushed content more attractive and practical. Through precise push, waste of resources is avoided, the efficiency of resource utilization is improved, and the user experience and satisfaction are improved.

[0007] Optionally, the analyzing of several digital publications on grain and oil quality testing to determine several publication information includes: Analyze several publications on grain and oil quality testing and determine the publication contents of several publications; Analyze the contents of the publications and determine target distribution areas for the publications; Classifying the publications according to target push areas of the publications to determine the publications in a certain region; Analyze the several regional publications to determine the publication types of the regional publications and the publication time of the regional publications; The plurality of publication information is determined according to the publication types of the plurality of regional publications, the publication times of the plurality of regional publications and the publication contents of the plurality of regional publications.

[0008] Through the above technical solution, through in-depth analysis of several publications, the target push areas of several publications are determined. According to the target push areas of different publications, the publications are classified by region to determine the regional characteristics of grain and oil quality testing in different regions. Different types of publications allow users to have more ways to understand the knowledge of grain and oil quality testing. Comprehensive information such as publication type, publication time and content can be used to fully grasp the latest developments, standards and specifications in the field of grain and oil quality testing.

[0009] Optionally, analyzing the user information, determining the push target factory, determining the production information according to the push target factory, and determining the historical information of several similar factories according to the production information includes: Analyze the user information to determine user account information; Determine the push target factory according to the user account information; Determine the target factory information according to the push target factory; Analyze the target factory information to determine the target factory address information, target factory inspection information and target factory production process; Determine the target factory inspection standard and target factory inspection process according to the target factory inspection information; Determine the production information of the target factory according to the target factory address information, the target factory inspection standard, the target factory inspection process and the target factory production process; According to the production information, matching several similar factory information in a preset database; According to the information of the plurality of similar factories, historical information of the plurality of similar factories is determined.

[0010] Through the above technical solution, by analyzing user information, the user account information is accurately determined, and then the target factory is accurately determined, which improves the accuracy and pertinence of information push. In-depth analysis of the basic information of the target factory, understanding the address information, inspection information and production process of the target factory, and achieving a comprehensive understanding and mastery of the target factory. By matching similar factory information in the preset database and determining the historical information of these similar factories, more accurate data reference is provided for the publication push of the target factory.

[0011] Optionally, determining the difference information according to the plurality of publication information and the historical information includes: Analyze the historical information of the several similar factories to determine the factory address information of the several similar factories; Determine the region to which the factory belongs according to the factory address information; Filter local publication information according to the regions where the several similar factories are located and several publication information; Analyze historical information of the several similar factories, determine factory inspection standards of the several similar factories and factory inspection processes of the several similar factories; Determine standard difference information based on the local publication information and the factory testing standards of the several similar factories; Determine process difference information based on the local publication information and the factory inspection processes of the several similar factories; The standard difference information and the process difference information are combined into difference information.

[0012] Through the above technical solution, by analyzing the factory address information of similar factories, the region to which the factory belongs is determined, and targeted analysis of the region is carried out to improve the accuracy and regionality of the analysis. According to the region to which the factory belongs and the publication information, the publication information related to the local area is screened out to provide the factory with more regional and practical reference materials. By analyzing the testing standards and testing processes of similar factories and comparing them with the relevant standards in the local publication information, the differences in the factory's testing standards and processes can be clarified.

[0013] Optionally, analyzing the historical viewing information to determine the viewing content and user acceptance of the plurality of similar factories includes: Analyze the historical viewing information to determine viewing time data and viewing page number data; Analyze the viewing time data to determine the specific content to be stayed and the specific content to be fast-forwarded; Analyze the page view data to determine specific content to be read and specific content to be skipped; Merging the specific stay content and the specific reading content into the user concerned content; Merging the specific fast-forward content and the specific skipped content into user indifference content; Analyze the user's attention content, the viewing time data, and the viewing page data to determine the proportion of attention content; Determine the video viewing rate and article reading rate based on the percentage of the concerned content; Determining the viewing content according to the content that the user pays attention to and the content that the user is indifferent to; The user acceptance is determined according to the video viewing rate and the article reading rate.

[0014] Through the above technical solution, by analyzing the viewing time data and the number of pages viewed data, the specific behaviors of users in the viewing or reading process, such as staying, fast-forwarding, reading and skipping, can be accurately identified, and then the content that users pay attention to and the content that they are indifferent to can be distinguished. By analyzing the proportion of content that is in attention and the proportion of indifferent content, the quality and attractiveness of videos and articles can be objectively evaluated, and it can be determined which parts are popular and which parts need improvement. The determination of video viewing rate and article reading rate provides specific indicators for measuring user acceptance, which facilitates comparative analysis across time and content.

[0015] Optionally, the user acceptance is determined according to the video viewing rate and the article reading rate, referring to the following formula: ; in, represents the user acceptance, Indicates the viewing rate of the video. represents the reading rate of the article, represents the influence coefficient of the video viewing rate, Represents the influence coefficient of the article reading rate.

[0016] Through the above technical solution, the user acceptance is calculated by substituting the video viewing rate and article reading rate into the user acceptance calculation formula, taking into account the two indicators of video viewing rate and article reading rate, and the influence coefficient and By setting the content content, the weights of the two in user acceptance evaluation can be flexibly adjusted to more comprehensively reflect the user's overall acceptance of the content.

[0017] Optionally, the determining and pushing a push plan to the push target factory according to the viewing content, the production information, the user acceptance and the plurality of publication information includes: Obtaining a preset acceptance degree, comparing the user acceptance degree with the preset acceptance degree, and determining whether the user acceptance degree is lower than the preset acceptance degree; If the user acceptance is lower than the preset acceptance, analyzing the user indifferent content, the user concerned content and the information of the plurality of publications to determine a content push adjustment plan; Determine a prediction and push plan based on the factory production process and the information of the plurality of publications; Summarizing the content push adjustment plan and the predicted push plan into a push plan; Push is performed according to the push scheme.

[0018] Through the above technical solution, by comparing the user acceptance with the preset acceptance, it is possible to timely discover the user's dissatisfaction or indifference to the current push content. By accurately pushing the content that the user is interested in, the user's satisfaction and retention rate can be effectively improved. The content push is adjusted according to the user's current behavior and preferences, and the future push plan is predicted in combination with the factory production process and publication information. Ensure that the pushed content meets the user's current needs.

[0019] Optionally, the analyzing the user indifferent content, the user concerned content and the plurality of publication information to determine the content push adjustment plan includes: Determine a video content adjustment plan according to the specific fast-forward content in the user indifferent content, the specific stay content in the user concerned content, and the plurality of publication information; Determine an article content adjustment plan according to the specific reading content in the user's attention content, the specific skipped content in the user's indifference content, and the plurality of publication information; The content push adjustment plan is determined according to the video content adjustment plan and the article content adjustment plan.

[0020] Through the above technical solution, by deeply analyzing the specific fast-forward parts in the content that users are not interested in and the specific stay parts in the content that users are interested in, combined with publication information, the parts of the video content that need to be adjusted or optimized can be accurately identified. Similarly, the specific reading parts in the content that users are interested in and the specific skipped parts in the content that users are not interested in can be analyzed to accurately find out the problems or deficiencies in the article content. According to the video content adjustment plan and the article content adjustment plan, the pushed content is finely adjusted to better meet the needs and preferences of users and improve the user experience. Content push is adjusted according to the user's current behavior and preferences, and future push plans are predicted in combination with the factory production process and publication information to ensure that the pushed content meets the user's current needs.

[0021] Optionally, determining the video content adjustment plan according to the specific fast-forward content in the user indifferent content, the specific stop content in the user concerned content, and the plurality of publication information includes: Analyze the specific fast-forward content and determine a fast-forward operation; Determining the interest level of the fast-forward content according to the fast-forward operation; Analyze the specific stay content and determine the stay operation; Determining the interest level of the stay content according to the stay operation; Analyze the interest of the fast-forward content and the interest of the stay content to determine a number of time frames; Determining intercepted content according to the plurality of time frames; Matching the intercepted content with the local publication information to determine priority intercepted content; Determining the video content adjustment plan according to the priority intercepted content and the intercepted content; The determining of the article content adjustment plan according to the specific reading content in the user's attention content, the specific skipped content in the user's indifference content, and the plurality of publication information includes: Analyze the specific reading content and determine the reading operation; Determining the interest level of the reading content according to the reading operation; Analyze the specific skipped content and determine the skipped operation; Determining the interest level of the skipped content according to the skip operation; Analyze the interest level of the reading content and the interest level of the skipped content to determine a number of page numbers; Determining the reorganized content according to the number of page numbers; matching the reorganized content with the local publication information to determine priority reorganized content; The article content adjustment plan is determined based on the priority reorganization content and the reorganization content.

[0022] Through the above technical solution, by analyzing the user's fast-forward and stop operations, the user's interest in the video content is determined, and the content clips that the user is most interested in are intelligently intercepted for priority display, thereby improving the user's viewing experience and satisfaction. For content that the user is not interested in or is indifferent to, it is automatically filtered or reduced to prevent invalid information from interfering with the user and improve the efficiency of information acquisition. By matching the intercepted video content with local publication information, the priority content is determined to enhance the timeliness and relevance of the content. By quantifying the user's interest in the content, the effect of content adjustment is scientifically adjusted to provide data support for subsequent optimization strategies.

[0023] Optionally, determining the prediction push scheme according to the factory production process and the plurality of publication information includes: Analyze the production process of the target factory and determine several processing stages; Determining processing materials for the plurality of processing stages according to the plurality of processing stages; Analyze the processing materials and the local publication information to determine relevant information of the processing materials; Determining that no information is involved based on the relevant information and the content push adjustment plan; The predicted push solution is determined according to the uninvolved information.

[0024] Through the above technical solutions, the production process of the target factory is deeply analyzed, several processing stages and the processing materials used in each stage are determined, and every link in the production process is understood. After mastering the relevant information of the processing materials, a prediction and push plan is formulated, that is, digital publications are pushed based on this information. This allows users to have a more comprehensive understanding of the relevant knowledge of production and enhance the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0026] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of a method for disseminating and pushing digital publication content provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0029] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0030] Existing technologies for the dissemination and push of digital publishing content cover cross-platform reading, digital copyright protection, personalized recommendations, social media dissemination, cloud computing and big data applications, which improve user experience, expand the scope of dissemination, and promote the dissemination of content.

[0031] At present, the dissemination and push of digital publications on grain and oil quality inspection lacks personalized recommendations, making it difficult to predict users' specific needs and update push content in a timely manner. User acceptance is low, and content push efficiency is low.

[0032] Based on this, the present application provides a method for disseminating and pushing digital publishing content. By analyzing several publications, the publishing areas, publishing times, and publishing contents of several publications are determined, and several publications are determined to be more regional and timely. By analyzing user information and factory production information, the target factory for push is determined to ensure that the pushed content matches the actual needs and concerns of the factory. Combined with the historical information of similar factories, the push content is further refined to make it closer to the actual application scenarios of the target factory. Analyze the historical viewing information and user acceptance of similar factories to understand which types of content similar factories are more interested in, thereby optimizing the push plan, improving the user acceptance of the target factory, and making the pushed content more attractive and practical. Through precise push, waste of resources is avoided, the efficiency of resource use is improved, and at the same time, the user experience and satisfaction are improved.

[0033] Figure 1 This is a schematic diagram of an application scenario provided by the present application. When disseminating and pushing digital publication content on grain and oil quality testing, the method provided by the present application can be applied to achieve personalized push of digital publication content and avoid waste of resources.

[0034] Specifically, the method provided in the present application is applied to any server, and the server interacts with the information management system.

[0035] Through the information management system, we can obtain several publications on grain and oil quality testing, analyze several publications, determine the publishing area, publishing time, and publishing content of several publications, and determine that several publications are more regional and timely. By analyzing user information and factory production information, we can determine the target factory for push notifications, and ensure that the pushed content matches the actual needs and concerns of the factory. Combined with the historical information of similar factories, we can further refine the push content to make it closer to the actual application scenarios of the target factory. We can analyze the historical viewing information and user acceptance of similar factories to understand which types of content similar factories are more interested in, so as to optimize the push plan, improve the user acceptance of the target factory, and make the pushed content more attractive and practical. Through precise push notifications, we can avoid waste of resources, improve the efficiency of resource use, and improve the user experience and satisfaction.

[0036] For specific implementation methods, please refer to the following embodiments.

[0037] Figure 2 This is a flow chart of a method for disseminating and pushing digital publication content provided in an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Acquire and analyze several digital publications on grain and oil quality testing, and determine some publication information.

[0038] Digital publications can be digitized publications related to grain and oil quality testing, such as reports generated by monitoring or testing in the fields of grain, agriculture, and food industry.

[0039] The publication information may be the publication information of digital publications related to grain and oil quality testing, such as the publication time, publication area, etc.

[0040] Specifically, before determining the push plan, first analyze several publications on grain and oil quality testing, determine the information of several publications, and fully understand the content, type, publication time, etc. of several publications, so that the push plan can be determined more accurately and meticulously.

[0041] Therefore, several digital publications on grain and oil quality inspection are obtained from the information management system, several digital publications on grain and oil quality inspection are analyzed, file formats of several digital publications are identified, and publication types of several digital publications are determined, such as text, video, etc.

[0042] Extract several digital publications on grain and oil quality inspection from the information management system, analyze several digital publications, and determine several publication information through content analysis and retrieval technology.

[0043] S202, obtaining and analyzing user information, determining a push target factory, determining production information based on the push target factory, and determining historical information of several similar factories based on the production information.

[0044] The user information may be the user's account information.

[0045] The push target factory may be a target food factory that needs to carry out digital publication dissemination and push.

[0046] The production information may be food information when the target factory produces food, such as the types of products produced by the factory.

[0047] A similar factory may be a factory whose production information is similar or identical to that of the push target factory.

[0048] The historical information may be data information when users of similar factories viewed historical publications.

[0049] Specifically, before determining the push plan, first determine the factory to be pushed and clarify the push target. Then analyze the information of the target factory and match several similar factories based on the information of the target factory. By analyzing the historical information of similar factories, content can be pushed to the target factory in a more path-oriented and organized manner.

[0050] Therefore, the user information is analyzed, and the user's account information is determined through natural language processing, and then the factory information to which the user belongs is determined through the account information. The factory is the push target factory. The target factory information is analyzed, and the production information of the target factory is determined through natural language processing.

[0051] Because publications need to be pushed to the target push factory, but there is no historical data of the target push factory, it is difficult to determine the needs of the target push factory, so a database is set up in advance. This preset database stores the factory information of several factories. By analyzing the historical information of several factories similar to the target push factory, the push plan is determined.

[0052] Therefore, the production information of the target factory is matched with the factory information in the preset database to determine several similar factory information, and then the several similar factory information is analyzed, and the historical information of several similar factories is determined through natural language processing.

[0053] S203: Determine difference information based on the publication information and historical information, and determine historical viewing information related to the difference information based on the difference information.

[0054] The difference information may be information that is different between information in several publications and historical information of several similar factories, such as testing standards.

[0055] The historical viewing information may be information on digital publications of grain and oil quality inspections viewed by several similar factories. Digital publications may be content published and distributed in digital form, typically including text and video, etc.

[0056] Specifically, before determining the push plan, the differences between the historical information of similar factories and the information of several publications are analyzed. Through this step, the content that needs to be analyzed can be accurately located while narrowing the scope of analysis.

[0057] Therefore, firstly, the historical information of several similar factories is analyzed, and their address information is determined through natural language processing methods, such as entity recognition algorithms, and the region to which the factory belongs is determined based on this. Then, the region to which the factory belongs is matched with the information of several publications to filter out the local publication information.

[0058] Then, the historical information of these factories is analyzed, and their factory inspection standards and factory inspection processes are determined through natural language processing methods, such as keyword extraction algorithms. After that, the local publication information is compared with the factory inspection standards and factory inspection processes to determine the differences between the local publication information and the factory inspection standards and factory inspection processes, and then the information corresponding to the differences is determined as difference information.

[0059] S204: Analyze historical viewing information to determine viewing content and user acceptance of several similar factories.

[0060] The viewing content may be different types of actual viewing content, such as videos and articles, etc., that are viewed by users of a number of similar factories.

[0061] User acceptance can be the acceptance of the viewing content by several similar factories.

[0062] Specifically, the historical viewing information of similar factories is analyzed, and the user acceptance is determined based on the viewing content in the historical viewing information. Through this step, the acceptance level of historical publications can be clearly understood, and the content can be adjusted better based on the acceptance level.

[0063] Therefore, analyze the historical viewing information of several similar factories, analyze the historical viewing information through natural language processing means or video analysis technology, and determine the specific viewing time data and viewing page number data. Analyze the viewing time data and viewing page number data, analyze the viewing time data and viewing page number data through natural language processing means and video analysis technology, and combine user operations to determine the content that users pay attention to and the content that users are indifferent to. Then, based on the content that users pay attention to, the number of pages viewed, and the viewing time data, determine the proportion of content that users pay attention to through comparative analysis. Similarly, based on the content that users are indifferent to, the number of pages viewed, and the viewing time data, determine the proportion of indifferent content through comparative analysis. Then determine the video viewing rate and article reading rate.

[0064] Finally, user acceptance is determined through mathematical analysis based on the video viewing rate and article reading rate.

[0065] S205: Determine a push plan for the target factory and push it based on the viewing content, production information, user acceptance and certain publication information.

[0066] The push plan may be a publication push plan that is adjusted by analyzing historical information of several similar factories.

[0067] Specifically, we analyze viewing content, production information, user acceptance and certain publication information, so that content adjustment plans and predictive push plans can be justified, push plans can be determined more accurately, and user acceptance can be improved.

[0068] Because it is difficult to judge the actual degree of user acceptance of content only through user acceptance, an acceptance degree is set in advance. This preset acceptance degree is determined by analyzing a large amount of data and can more clearly determine the user's acceptance degree.

[0069] Therefore, the user acceptance is compared with the preset acceptance to determine whether the user acceptance is lower than the preset acceptance. When the user acceptance is lower than the preset acceptance, the viewing content of several similar factories is analyzed to extract the user-focused content and the user-indifferent content. The user-focused content, the user-indifferent content and several publication information are analyzed, and the content push adjustment plan is determined by natural language processing and video analysis technology combined with user operations. The production information and the content push adjustment plan are analyzed, and the uninvolved information is determined through comparative analysis. Based on the uninvolved information and several publication information, the prediction push plan is determined.

[0070] Through the method provided in this embodiment, by analyzing several publications, the publishing area, publishing time, and publishing content of several publications are determined, and several publications are determined to be more regional and timely. By analyzing user information and factory production information, the target factory for push is determined to ensure that the pushed content matches the actual needs and concerns of the factory. Combined with the historical information of similar factories, the push content is further refined to make it closer to the actual application scenarios of the target factory. Analyze the historical viewing information and user acceptance of similar factories to understand which type of content similar factories are more interested in, so as to optimize the push plan, improve the user acceptance of the target factory, and make the pushed content more attractive and practical. Through precise push, waste of resources is avoided, the efficiency of resource use is improved, and the user experience and satisfaction are improved.

[0071] In some embodiments, several publications on grain and oil quality testing are analyzed to determine the publication contents of the several publications; the publication contents of the several publications are analyzed to determine the target push areas of the several publications; according to the target push areas of the several publications, the several publications are classified to determine several regional publications; several regional publications are analyzed to determine the publication types of the regional publications and the publication time of the regional publications; according to the publication types of the several regional publications, the publication time of the several regional publications and the publication contents of the several regional publications, several publication information is determined.

[0072] The target push area may be an area where a number of publications are planned to be pushed.

[0073] Regional publications can be publications that are selected based on different target push areas.

[0074] The publication type can be a classification of several publications, such as video and text.

[0075] Specifically, before determining the push plan, first analyze several publications on grain and oil quality testing, determine the information of several publications, and fully understand the content, type, publication time, etc. of several publications, so that the push plan can be determined more accurately and meticulously.

[0076] Therefore, we analyze several publications on grain and oil quality testing, extract the titles of several publications through natural language processing methods, such as keyword extraction algorithms, analyze the titles, and determine the publication content of several publications. We analyze the publication content of several publications, and determine the target push areas of several publications through content analysis. According to the different target push areas of several publications, we classify several publications according to different push target areas to obtain regional publications in different regions.

[0077] By analyzing the file formats of regional publications in different regions, the publication types of regional publications can be determined. By analyzing metadata, the publication time of regional publications can be determined.

[0078] Finally, the publication type, publication time and publication content of several regional publications are merged into several publication information.

[0079] Through the method provided by this embodiment, through in-depth analysis of several publications, the target push areas of several publications are determined. According to the target push areas of different publications, the publications are classified by region to determine the regional characteristics of grain and oil quality detection in different regions. Different types of publications allow users to have more ways to understand the knowledge of grain and oil quality detection. Comprehensive information such as publication type, publication time and content can be used to fully grasp the latest developments, standards and specifications in the field of grain and oil quality detection.

[0080] In some embodiments, user information is analyzed to determine user account information; based on the user account information, a target factory to be pushed is determined; based on the pushed target factory, target factory information is determined; the target factory information is analyzed to determine the target factory address information, target factory inspection information and target factory production process; based on the target factory inspection information, the target factory inspection standards and target factory inspection process are determined; based on the target factory address information, the target factory inspection standards, the target factory inspection process and the target factory production process, the production information of the target factory is determined; based on the production information, a number of similar factory information in a preset database is matched; based on the number of similar factory information, historical information of a number of similar factories is determined.

[0081] The target factory information may be the food production information of the factory where the digital publication is planned to be pushed and the factory information itself.

[0082] The target factory inspection information may be the standards and process information for food inspection at the factory where the digital publication is planned to be pushed.

[0083] The target factory production process may be a specific process for producing products of the factory where the digital publication is planned to be pushed.

[0084] Specifically, before determining the push plan, first determine the factory to be pushed and clarify the push target. Then analyze the information of the target factory and match several similar factories based on the information of the target factory. By analyzing the historical information of similar factories, content can be pushed to the target factory in a more path-oriented and organized manner.

[0085] Therefore, the user information is analyzed by natural language processing to determine the user account information of the user. The user account information of the user is analyzed, the information module of the factory to which the user belongs in the user account information is extracted, the information module of the factory to which the user belongs is analyzed, the factory to which the user belongs is determined, and the factory to which the user belongs is determined as the push target factory. According to the information module of the factory to which the user belongs, the target factory information is determined by natural language processing. According to the target factory information, the target factory address information, the target factory detection information and the target factory production process are determined by keyword extraction.

[0086] According to the target factory detection information, keywords in the target factory detection information are extracted to determine the target factory detection standard and target factory detection process. Finally, the production information of the target factory is matched with the factory information in the preset database to determine several factories that belong to the same region and produce the same products as the target push factory. These factories are similar factories, and then several similar factory information is determined.

[0087] Analyze the information of several similar factories, extract the user information of several similar factories, and extract the historical information of several similar factories in a preset database based on the user information of several similar factories.

[0088] Through the method provided by this embodiment, by analyzing user information, the user account information is accurately determined, and then the target factory to be pushed is accurately determined, thereby improving the accuracy and pertinence of information push. The basic information of the target factory is deeply analyzed to understand the address information, detection information and production process of the target factory, so as to achieve a comprehensive understanding and mastery of the target factory. By matching similar factory information in the preset database and determining the historical information of these similar factories, a more accurate data reference is provided for the publication push of the target factory.

[0089] In some embodiments, historical information of several similar factories is analyzed to determine factory address information of several similar factories; the region to which the factory belongs is determined based on the factory address information; local publication information is screened based on the region to which the factory belongs and several publication information; historical information of several similar factories is analyzed to determine factory inspection standards of several similar factories and factory inspection processes of several similar factories; standard difference information is determined based on local publication information and factory inspection standards of several similar factories; process difference information is determined based on local publication information and factory inspection processes of several similar factories; and the standard difference information and process difference information are merged into difference information.

[0090] The local publication information may be information about publications in the same target push area and in the same area as that of several similar factories.

[0091] The standard difference information may be information that there are differences between the testing standards in several publications and the testing standards of several similar factories.

[0092] Process difference information can be information about differences between the testing processes in several publications and the testing processes in several similar factories. Specifically, before determining the push plan, by analyzing the differences between the historical information of similar factories and the information of several publications, the historical viewing information related to the difference information is determined according to the differences in information. Through this step, the content that needs to be analyzed is accurately located while narrowing the scope of analysis.

[0093] Therefore, the historical information of several similar factories is analyzed through the entity recognition algorithm and keyword extraction algorithm in natural language processing technology to determine the factory address information of several similar factories. According to the factory address information, the factory address information is compared with the map to determine the region to which the factory belongs. The regions to which the factories of several similar factories belong are matched with the target push regions of several publication information and the regions of regional publications in several different regions, and the publications in the same region are screened out, and then the publications in the same region are determined as local publication information.

[0094] According to the historical information of several similar factories, the keyword extraction algorithm in natural language processing technology is used to extract the inspection information of several similar factories in the historical information, and determine the factory inspection standards and factory inspection processes of several similar factories. Then, the local publication information is compared with the factory inspection standards of several similar factories to determine the information where there are differences between the two, which is the standard difference information. Similarly, the local publication information is compared with the factory inspection processes of several similar factories to determine the information where there are differences between the two, which is the standard process difference information.

[0095] Finally, the standard difference information and process difference information are merged into difference information.

[0096] Through the method provided in this embodiment, by analyzing the factory address information of similar factories, the region to which the factory belongs is determined, and targeted analysis is performed on the region to improve the accuracy and regionality of the analysis. According to the region to which the factory belongs and the publication information, the publication information related to the local area is screened out to provide the factory with more regional and practical reference materials. By analyzing the testing standards and testing processes of similar factories and comparing them with the relevant standards in the local publication information, the differences in the factory's testing standards and processes are clarified.

[0097] In some embodiments, historical viewing information is analyzed to determine viewing time data and viewing page number data; viewing time data is analyzed to determine specific lingering content and specific fast-forwarding content; viewing page number data is analyzed to determine specific reading content and specific skipped content; specific lingering content and specific reading content are merged into user-focused content; specific fast-forwarded content and specific skipped content are merged into user-indifferent content; content that users focus on, viewing time data, and viewing page number data are analyzed to determine the proportion of focused content; based on the proportion of focused content, the video viewing rate and article reading rate are determined; based on the content that users focus on and the content that users are indifferent to, the viewing content is determined; based on the content that users focus on and the content that users are indifferent to, the viewing content is determined; based on the video viewing rate and article reading rate, the user acceptance is determined.

[0098] The viewing time data may be video data and viewing data about a user viewing video publications, such as total viewing time, total video time, etc.

[0099] The viewed page data may be article data and reading data about text publications viewed by the user, such as the total number of viewed pages, the total number of article pages, and the like.

[0100] The specific pause content may be the specific content corresponding to the pause operation performed by the user when watching video publications. For example, the pause operations include pause, normal speed play, etc.

[0101] The specific fast-forward content may be the specific content corresponding to the fast-forward operation performed by the user when viewing a video publication. For example, the fast-forward operation includes fast-forward, double-speed playback, and the like.

[0102] The specific reading content may be the specific content corresponding to the reading operation performed by the user when viewing a text publication, for example, the reading operation includes pause, normal sliding, etc.

[0103] The specific skipped content may be the specific content corresponding to the skip operation performed by the user when viewing a text publication, for example, the skip operation includes skipping, quick sliding, etc.

[0104] The user's attention content may be the content corresponding to the user's pause operation or reading operation when the user watches video or text publications.

[0105] User cold content may be the content corresponding to a user performing a fast-forward operation or a skip operation when viewing a video or text publication.

[0106] The proportion of content attention may be the ratio of the content that a user pays attention to when watching video and text publications to the total content.

[0107] The cold content ratio may be the ratio of cold content to the total content when users watch video and text publications.

[0108] The video viewing rate can be the ratio of the time that users pay attention to the content when watching video publications to the total video time.

[0109] The article reading rate can be the ratio of the number of pages that users pay attention to when reading text publications to the total number of pages in the article.

[0110] Specifically, by analyzing the historical viewing information of similar factories, we can determine the user attention content and user indifference content of similar factories, and then determine the user acceptance. Through this step, we conduct a rigorous analysis of the historical viewing information to provide more diversified data references for the determination of the push plan.

[0111] Therefore, we analyzed the historical viewing information of several similar factories, extracted the data of users watching video and text publications through natural language processing, and determined the viewing time data and viewing page number data.

[0112] Analyze viewing time data, and extract the user's operations when viewing video publications, the corresponding time frames of the operations, and the corresponding content of the time frames through event monitoring technology and computer vision processing technology, and determine the specific content to stay on and the specific content to fast forward. Analyze viewing page data through article embedding technology and natural language processing methods to determine the operation of viewing article publications, and determine the specific content to read and the specific content to skip through the user's operations when viewing video publications, the corresponding page numbers of the operations, and the corresponding content of the page numbers.

[0113] Then, the specific stay content and the specific reading content are combined into the user's attention content, and the specific fast-forward content and the specific skipped content are combined into the user's cold content. The corresponding length of the user's attention content is compared with the total length of video publications to determine the proportion of the corresponding length of the user's attention content to the total length of video publications. The viewing progress of the video is determined based on the proportion, and the viewing progress is the video viewing rate.

[0114] Compare the number of pages corresponding to the content that the user is interested in with the total number of pages of text publications to determine the ratio of the number of pages corresponding to the content that the user is interested in to the total number of pages of text publications. Determine the reading progress of the article based on the ratio, and the reading progress is the article reading rate.

[0115] Then, the user's attention content and user's indifference content are combined into the user's viewing content. Finally, according to the video viewing rate and article reading rate, the user's acceptance is determined through mathematical processing. Through the method provided by this embodiment, by analyzing the viewing time data and the number of pages viewed data, the specific behaviors of users in the viewing or reading process, such as staying, fast forwarding, reading and skipping, etc., can be accurately identified, thereby distinguishing the content that users pay attention to and the content that they are indifferent to. By analyzing the proportion of content that users pay attention to and the proportion of indifferent content, the quality and attractiveness of videos and articles can be objectively evaluated to determine which parts are popular and which parts need to be improved. The determination of video viewing rate and article reading rate provides specific indicators for measuring user acceptance, which facilitates comparative analysis across time and content.

[0116] In some embodiments, user acceptance is determined based on the video viewing rate and article reading rate, referring to formula (1): (1); in, Indicates user acceptance. Indicates the video viewing rate. Indicates the article reading rate, Indicates the influence coefficient of video viewing rate, Indicates the influence coefficient of article reading rate.

[0117] Specifically, by quantifying user acceptance through mathematical formulas, we can more clearly and intuitively understand the acceptance of the content.

[0118] Therefore, the video viewing rate and article reading rate are substituted into the user acceptance calculation formula, and the user acceptance is determined through mathematical calculation. and The specific value of can be obtained through experiments, and and The sum of is 1.

[0119] Through the method provided in this embodiment, the user acceptance is calculated by substituting the video viewing rate and the article reading rate into the user acceptance calculation formula, taking into account the two indicators of video viewing rate and article reading rate, and the influence coefficient and By setting the content content, the weights of the two in user acceptance evaluation can be flexibly adjusted to more comprehensively reflect the user's overall acceptance of the content.

[0120] In some embodiments, a preset acceptance degree is obtained, and the user acceptance degree is compared with the preset acceptance degree to determine whether the user acceptance degree is lower than the preset acceptance degree; if the user acceptance degree is lower than the preset acceptance degree, the user indifferent content, the user concerned content and a number of publication information are analyzed to determine a content push adjustment plan; a predicted push plan is determined based on the factory production process and a number of publication information; the content push adjustment plan and the predicted push plan are summarized as a push plan; and push is performed according to the push plan. The content push adjustment plan can be an adjustment plan for pushing video publications and text publications.

[0121] The predictive push plan can be a publication push plan based on the inspection process and inspection standards in the factory production process.

[0122] Specifically, by comparing with the preset acceptance level, it is determined whether the user acceptance level is lower than the preset acceptance level. Then, the historical viewing information is specifically analyzed to determine the content adjustment plan for different publication types and the prediction push plan, so that the push plan is more personalized and comprehensive.

[0123] Therefore, the user acceptance is compared with the preset acceptance to determine whether the user acceptance is lower than the preset acceptance. When the user acceptance is lower than the preset acceptance, the user indifferent content and the user concerned content are analyzed, and the specific operations of fast-forwarding content and skipping content in the user indifferent content are extracted through event monitoring technology. Analyze the specific operations, and different operations correspond to different content interests. Then, according to the content interest and some publication information, adjust the pushed content. For example, the publication content corresponding to the content with extremely high interest is mainly pushed, and the publication content corresponding to the content with extremely low interest is not pushed. Then determine the content push adjustment plan.

[0124] The factory production process is analyzed through the keyword extraction algorithm in the natural language processing method to determine several processing stages and the processing materials of several processing stages. The processing materials are matched with the publication information to determine the relevant information of the processing materials. Finally, the relevant information of the processing materials is matched with the information of several publications to determine the information related to the processing materials that is not involved in the content push adjustment plan, match the information related to the processing materials that is not involved with the publication information, determine the content in the publication information that corresponds to the information related to the processing materials that is not involved with the content push adjustment plan, and determine the content as the prediction push plan.

[0125] Through the method provided by this embodiment, by comparing the user acceptance with the preset acceptance, it is possible to timely discover the user's dissatisfaction or indifference to the current pushed content. By accurately pushing content that the user is interested in, the user's satisfaction and retention rate are effectively improved. Content push is adjusted according to the user's current behavior and preferences, and future push plans are predicted in combination with the factory production process and publication information. Ensure that the pushed content meets the user's current needs.

[0126] In some embodiments, a video content adjustment plan is determined based on specific fast-forward content in user-indifferent content, specific pause content in user-interested content, and information of several publications; an article content adjustment plan is determined based on specific reading content in user-interested content, specific skipped content in user-indifferent content, and information of several publications; a content push adjustment plan is determined based on the video content adjustment plan and the article content adjustment plan.

[0127] The video content adjustment plan may be a plan for adjusting the push content of video publications.

[0128] The article content adjustment plan may be a plan for adjusting the push content of text publications.

[0129] Specifically, we analyze the content that users are not interested in and the content that users are interested in, and determine the video content adjustment method and article content adjustment plan based on the content that users are not interested in and the content that users are interested in. This makes content adjustment more targeted.

[0130] Therefore, the specific fast-forward content in the user's indifferent content is analyzed through event monitoring technology to determine several specific operations of the specific fast-forward content. Similarly, the specific stay content in the user's attention content is analyzed through event monitoring technology to determine several specific operations of the specific stay content. Then, according to the several specific operations of the specific fast-forward content and the several specific operations of the specific stay content and the several publication information, the several publication information is adjusted to determine the video content adjustment plan.

[0131] The specific skipped content in the user's indifferent content is analyzed through article tracking technology to determine several specific operations of the specific skipped content. Similarly, the specific reading content in the user's attention content is analyzed through article tracking technology to determine several specific operations of the specific reading content. Then, based on the several specific operations of the specific skipped content and the several specific operations of the specific reading content and the several publication information, the several publication information is adjusted to determine the article content adjustment plan.

[0132] Through the method provided in this embodiment, by deeply analyzing the specific fast-forward parts in the content that users are not interested in and the specific stay parts in the content that users are interested in, combined with the publication information, the parts of the video content that need to be adjusted or optimized are accurately identified. Similarly, the specific reading parts in the content that users are interested in and the specific skipped parts in the content that users are not interested in are analyzed to accurately find out the problems or deficiencies in the article content. According to the video content adjustment plan and the article content adjustment plan, the pushed content is finely adjusted to better meet the needs and preferences of users and improve the user experience. Content push is adjusted according to the user's current behavior and preferences, and future push plans are predicted in combination with the factory production process and publication information to ensure that the pushed content meets the user's current needs.

[0133] In some embodiments, specific fast-forward content is analyzed to determine a fast-forward operation; based on the fast-forward operation, the interest of the fast-forward content is determined; specific stop content is analyzed to determine a stop operation; based on the stop operation, the interest of the stop content is determined; the interest of the fast-forward content and the stop content are analyzed to determine a number of time frames; based on the number of time frames, the intercepted content is determined; the intercepted content is matched with local publication information to determine priority intercepted content; based on the priority intercepted content and the intercepted content, a video content adjustment plan is determined; based on the specific reading content in the user-focused content, the specific skipped content in the user-indifferent content, and a number of publication information, an article content adjustment plan is determined, including: analyzing specific reading content to determine a reading operation; based on the reading operation, determining the interest of the reading content; analyzing specific skipped content to determine a skip operation; based on the skip operation, determining the interest of the skipped content; analyzing the interest of the reading content and the interest of the skipped content to determine a number of page numbers; based on the number of page numbers, reorganized content is determined; the reorganized content is matched with local publication information to determine priority reorganized content; based on the priority reorganized content and the reorganized content, an article content adjustment plan is determined.

[0134] The fast forward operation may be a specific operation of the user performing fast forward when watching a video publication, such as playing at double speed, pressing the fast forward key, etc. The interest level of the fast forward content may be the interest level of the user in the content of the video publication on which the fast forward operation is performed. The stop operation may be a specific operation of the user performing stop operation when watching a video publication, such as pausing, playing at normal speed, etc. The interest level of the stop content may be the interest level of the user in the content of the video publication on which the stop operation is performed. The intercepted content may be the content corresponding to several time frames. The priority intercepted content may be the local content in the content corresponding to several time frames. The reading operation may be a specific operation of the user performing reading when watching a text publication, such as stop reading, normal sliding reading, etc. The interest level of the reading content may be the interest level of the user in the content of the text publication on which the reading operation is performed. The skip operation may be a specific operation of the user performing skip operation when watching a text publication, such as selecting a chapter through the catalog, fast sliding reading, etc. The interest level of the skip content may be the interest level of the user in the content of the text publication on which the skip operation is performed. The reorganized content may be the content corresponding to several page numbers. The priority reorganized content may be the local content among the content corresponding to several pages.

[0135] Specifically, by analyzing the specific operations of users on content that they pay attention to and content that they are indifferent to, specific content adjustment plans are determined based on the specific operations, making the content adjustment plans more refined.

[0136] Therefore, the specific fast-forward content is analyzed, the screen conversion speed during viewing is extracted, and the fast-forward operation is determined based on the screen conversion speed. For example, when there is a huge difference in the screen content, it means that a fast-forward operation has been performed. When the screen conversion speed is faster than the original video screen conversion speed, it means that the video is played at a double speed.

[0137] The user's operations of watching video publications and article publications are classified, and then the user's interest in the content is judged based on the user's feedback. When the user performs different operations, the user's different interests in the content can be reflected, so a content interest determination rule can be set according to the user operation.

[0138] Analyze the fast-forward operation, determine the operation type, and determine the interest in the fast-forward content based on the operation type. For example, when playing at double speed, it means that the user only needs to understand the general content of the part played at double speed, and wants to understand but not too much, so the content interest is low. When fast-forwarding, it means that the user does not need the content of this part, and the content interest is extremely low. The interest in the content of the specific operation can be further refined according to the actual situation.

[0139] Similarly, the specific pause content is analyzed, the screen transition speed during viewing is extracted, and the pause operation is determined according to the screen transition speed. For example, when the screen is still, it indicates a pause operation. When the screen transition speed is consistent with the original video screen transition speed, it indicates normal speed playback.

[0140] Analyze the pause operation, determine the operation type, and determine the interest in the pause content based on the operation type. For example, when performing a pause operation, extract the user screen operation. When the user uses the device to slide on the interface, it means that the user attaches great importance to this part of the content and has a very high interest in the content. When the user does not operate the interface for a long time, it means that the user has a general interest in this part of the content. When playing at normal speed, it means that the user attaches importance to this part of the content and has a high interest in the content. The interest in the content of the specific operation can be further refined according to the actual situation.

[0141] Analyze the fast-forward content interest and the stay content interest, extract all time frames corresponding to different content interest, and determine a number of time frames based on all time frames. Analyze a number of time frames, determine the video content corresponding to a number of time frames, and determine the video content corresponding to a number of time frames as the new video content after the interception operation, and the new video content is the intercepted content. Match the intercepted content with the local publication information to determine the content related to the intercepted content of the local publication, and this part of the content is the priority intercepted content. Then edit the original video according to the priority intercepted content and the intercepted content, and determine the video content adjustment plan.

[0142] Analyze the specific reading content, extract the page number change speed during viewing, and determine the reading operation based on the page number change speed. For example, when the page number remains unchanged for a long time, it means that the user has paused. When the page number change speed is at a normal change speed, it means that the user is reading normally.

[0143] Analyze reading operations, determine the operation type, and determine the interest in reading content based on the operation type. For example, when performing a pause operation, extract the user screen operation. When the user checks the content of the article, it means that the user attaches great importance to this part of the content and has a very high interest in the content. When the user does not operate the content of the article for a long time, it means that the user has a general interest in this part of the content. When reading normally, it means that the user attaches importance to this part of the content and has a high interest in the content. The interest in the content of the specific operation can be further refined according to the actual situation.

[0144] Similarly, the specific skipped content is analyzed, the screen change speed during viewing is extracted, and the skip operation is determined based on the screen change speed. For example, when there is a huge difference in the screen content, it means that the page number selection skip operation is performed. When the screen change speed is faster than the normal change speed, it means that a fast sliding reading is performed.

[0145] Analyze the skip operation, determine the operation type, and determine the interest in the skipped content based on the operation type. For example, when reading quickly with a swipe, it means that the user only needs to understand the general content and does not need to be too detailed, and the content interest is low. When selecting a page number to skip, it means that the user does not need this part of the content and the content interest is extremely low. The specific operation can be further refined based on the actual situation.

[0146] Analyze the interest of fast-forward content and stay content, extract all page numbers corresponding to different content interests, and determine a number of page numbers based on all page numbers. Analyze a number of page numbers to determine the article content corresponding to the page numbers, and determine the video content corresponding to a number of page numbers as the new article content after the reorganization operation based on the article content. The new article content is the reorganized content. Match the reorganized content with the local publication information to determine the content related to the reorganized content of the local publication. This part of the content is the priority reorganized content. Then edit the original article based on the priority reorganized content and the reorganized content to determine the article content adjustment plan.

[0147] Through the method provided by this embodiment, by analyzing the user's fast forward and stop operations, the user's interest in the video content is determined, and the content clips that the user is most interested in are intelligently intercepted for priority display, thereby improving the user's viewing experience and satisfaction. For content that the user is not interested in or is indifferent to, it is automatically filtered or reduced to prevent invalid information from interfering with the user and improve the efficiency of information acquisition. By matching the intercepted video content with local publication information, the priority content is determined to enhance the timeliness and relevance of the content. By quantifying the user's interest in the content, the effect of content adjustment is scientifically adjusted to provide data support for subsequent optimization strategies.

[0148] In some embodiments, the production process of the target factory is analyzed to determine a number of processing stages; based on the number of processing stages, the processing materials for the number of processing stages are determined; the processing materials and local publication information are analyzed to determine the relevant information of the processing materials; an adjustment plan is pushed based on the relevant information and content to determine the uninvolved information; based on the uninvolved information, a predicted push plan is determined.

[0149] Processing materials can be materials needed to produce processed foods, such as flour.

[0150] The uninvolved information may be information that is not included in the content adjustment plan, such as raw material storage methods, etc.

[0151] Specifically, when determining the push plan, analyze the factory's production information, determine the predictive push plan, predict the content that users need and push it to users, so that users can understand more comprehensive knowledge and expand their knowledge horizons.

[0152] Therefore, the production process of the target factory is analyzed, and the processing stages of the target factory are determined through natural language processing. Then, the processing materials of the processing stages are determined again through natural language processing.

[0153] Match the processing materials of several processing stages with the local publication information to determine the relevant information of the processing materials in the local publication information. Then match the relevant information with the content push adjustment plan to determine the relevant information of the processing materials not included in the content push adjustment plan, that is, the uninvolved information. Finally, the uninvolved information and the content corresponding to several publications are determined as the content pushed by the predicted push plan, and pushed to the target push factory according to the predicted push plan.

[0154] Through the method provided in this embodiment, the production process of the target factory is deeply analyzed, several processing stages and the processing materials used in each stage are determined, and every link in the production process is understood. After mastering the relevant information of the processing materials, a prediction and push plan is formulated, that is, digital publications are pushed based on this information. This allows users to have a more comprehensive understanding of the relevant knowledge of production and enhance the user experience.

Claims

1. A method for disseminating and pushing digital publication content, characterized in that: include: Obtain and analyze several digital publications on grain and oil quality testing and determine some publication information; Acquire and analyze user information, determine a push target factory, determine production information based on the push target factory, and determine historical information of several similar factories based on the production information; Determine difference information according to the plurality of publication information and the historical information, and determine historical viewing information related to the difference information according to the difference information; Analyze the historical viewing information to determine viewing content and user acceptance of the several similar factories; According to the viewing content, the production information, the user acceptance and the information of the plurality of publications, a push plan for the push target factory is determined and pushed.

2. The method according to claim 1, characterized in that The analysis of several digital publications on grain and oil quality testing determines several publication information, including: Analyze several publications on grain and oil quality testing and determine the publication contents of several publications; Analyze the contents of the publications and determine target distribution areas for the publications; Classifying the publications according to target push areas of the publications to determine the publications in a certain region; Analyze the several regional publications to determine the publication types of the regional publications and the publication time of the regional publications; The plurality of publication information is determined according to the publication types of the plurality of regional publications, the publication times of the plurality of regional publications and the publication contents of the plurality of regional publications.

3. The method according to claim 1, characterized in that The analyzing user information, determining the push target factory, determining production information based on the push target factory, and determining historical information of several similar factories based on the production information, includes: Analyze the user information to determine user account information; Determine the push target factory according to the user account information; Determine the target factory information according to the push target factory; Analyze the target factory information to determine the target factory address information, target factory inspection information and target factory production process; Determine the target factory inspection standard and target factory inspection process according to the target factory inspection information; Determine the production information of the target factory according to the target factory address information, the target factory inspection standard, the target factory inspection process and the target factory production process; According to the production information, matching several similar factory information in a preset database; According to the information of the plurality of similar factories, historical information of the plurality of similar factories is determined.

4. The method according to claim 3, characterized in that: The determining of difference information according to the plurality of publication information and the historical information includes: Analyze the historical information of the several similar factories to determine the factory address information of the several similar factories; Determine the region to which the factory belongs according to the factory address information; Filter local publication information according to the regions where the several similar factories are located and several publication information; Analyze historical information of the several similar factories, determine factory inspection standards of the several similar factories and factory inspection processes of the several similar factories; Determine standard difference information based on the local publication information and the factory testing standards of the several similar factories; Determine process difference information based on the local publication information and the factory inspection processes of the several similar factories; The standard difference information and the process difference information are combined into difference information.

5. The method according to claim 4, characterized in that The analyzing the historical viewing information to determine the viewing content and user acceptance of the plurality of similar factories includes: Analyze the historical viewing information to determine viewing time data and viewing page number data; Analyze the viewing time data to determine the specific content to be stayed and the specific content to be fast-forwarded; Analyze the page view data to determine specific content to be read and specific content to be skipped; Merging the specific stay content and the specific reading content into the user concerned content; Merging the specific fast-forward content and the specific skipped content into user indifference content; Analyze the user's attention content, the viewing time data, and the viewing page data to determine the proportion of attention content; Determine the video viewing rate and article reading rate based on the percentage of the concerned content; Determining the viewing content according to the content that the user pays attention to and the content that the user is indifferent to; The user acceptance is determined according to the video viewing rate and the article reading rate.

6. The method according to claim 5, characterized in that The user acceptance is determined according to the video viewing rate and the article reading rate, referring to the following formula: ； in, represents the user acceptance, Indicates the viewing rate of the video. represents the reading rate of the article, represents the influence coefficient of the video viewing rate, Represents the influence coefficient of the article reading rate.

7. The method according to claim 6, characterized in that The step of determining and pushing a push plan to the push target factory according to the viewing content, the production information, the user acceptance and the plurality of publication information comprises: Obtaining a preset acceptance degree, comparing the user acceptance degree with the preset acceptance degree, and determining whether the user acceptance degree is lower than the preset acceptance degree; If the user acceptance is lower than the preset acceptance, analyzing the user indifferent content, the user concerned content and the information of the plurality of publications to determine a content push adjustment plan; Determine a prediction and push plan based on the factory production process and the information of the plurality of publications; Summarizing the content push adjustment plan and the predicted push plan into a push plan; Push is performed according to the push scheme.

8. The method according to claim 7, characterized in that The analyzing the user indifferent content, the user concerned content and the plurality of publication information to determine the content push adjustment plan includes: Determine a video content adjustment plan according to the specific fast-forward content in the user indifferent content, the specific stay content in the user concerned content, and the plurality of publication information; Determine an article content adjustment plan according to the specific reading content in the user's attention content, the specific skipped content in the user's indifference content, and the plurality of publication information; The content push adjustment plan is determined according to the video content adjustment plan and the article content adjustment plan.

9. The method according to claim 8, characterized in that The step of determining a video content adjustment plan based on the specific fast-forward content in the user indifferent content, the specific stop content in the user concerned content, and the plurality of publication information includes: Analyze the specific fast-forward content and determine a fast-forward operation; Determining the interest level of the fast-forward content according to the fast-forward operation; Analyze the specific stay content and determine the stay operation; Determining the interest level of the stay content according to the stay operation; Analyze the interest of the fast-forward content and the interest of the stay content to determine a number of time frames; Determining intercepted content according to the plurality of time frames; Matching the intercepted content with the local publication information to determine priority intercepted content; Determining the video content adjustment plan according to the priority intercepted content and the intercepted content; The determining of the article content adjustment plan according to the specific reading content in the user's attention content, the specific skipped content in the user's indifference content, and the plurality of publication information includes: Analyze the specific reading content and determine the reading operation; Determining the interest level of the reading content according to the reading operation; Analyze the specific skipped content and determine the skipped operation; Determining the interest level of the skipped content according to the skip operation; Analyze the interest level of the reading content and the interest level of the skipped content to determine a number of page numbers; Determining the reorganized content according to the number of page numbers; matching the reorganized content with the local publication information to determine priority reorganized content; The article content adjustment plan is determined based on the priority reorganization content and the reorganization content.

10. The method according to claim 7, characterized in that Determining a prediction push plan according to the factory production process and the plurality of publication information includes: Analyze the production process of the target factory and determine several processing stages; Determining processing materials for the plurality of processing stages according to the plurality of processing stages; Analyze the processing materials and the local publication information to determine relevant information of the processing materials; Determining that no information is involved based on the relevant information and the content push adjustment plan; The predicted push solution is determined according to the uninvolved information.

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