Research On Knowledge Resource Aggregation And Service Of WeChat Public Platform Oriented To User Knowledge Requirements

In the era of mobile Internet,WeChat public platform has already become a part of people's communication,leisure,study and life.With WeChat Official Accounts mainly aimed at spreading academic knowledge springing up,WeChat public platform has become an important way for users to get knowledge.Some multiple academic Official Accounts public comprehensive academic knowledge.Some Official Accounts of academic journals public professional academic knowledge.Some Official Accounts of university journals and libraries also have specialized "academic report","academic" and other columns,is used to publish academic lectures and academic frontiers of knowledge.WeChat Official Accounts release a large amount of general knowledge,professional general knowledge,frontier knowledge,specialized knowledge and academic knowledge through WeChat public platform,which can meet user knowledge requirement of knowledge.However,with the development of big data,artificial intelligence and other technologies,simple provision of knowledge resource can no longer meet the knowledge service requirements of users of WeChat public platform.In the era of intelligence,users have put forward higher requirements for knowledge service mode and knowledge quality.At present,the huge and varied account subjects of WeChat public platform lead to uneven information quality and serious information overload,and lack of scientific and efficient management and organization of massive knowledge resources.How to screen out the content that you really need and are interested in from the massive similar information is not only a problem facing the vast number of WeChat users,but also a problem that needs to be paid attention to and needs to be solved by WeChat public platform.In this paper,the theory and method of knowledge aggregation is introduced into the knowledge resource aggregation and service study of WeChat public platform.It proposes the user requirements oriented WeChat platform knowledge aggregation and public service system framework,builds the user portrait of WeChat public platform and analyzes the user knowledge requirements.For the word and sentence in articles respectively,knowledge resource aggregation methods is proposed based on tag clustering and based on the abstract generation.And base on different knowledge resource aggregation results,knowledge recommendation service and knowledge integration service of WeChat public platform are designed as knowledge service modes.Finally,the author puts forward the countermeasures to improve the knowledge aggregation and service ability of WeChat public platform.This paper mainly carries out the following aspects of research:(1)The knowledge aggregation and service system framework of the WeChat public platform oriented to user knowledge requirements.By analyzing the relationship among knowledge aggregation,knowledge service and user requirements,the necessity and feasibility of knowledge aggregation of WeChat public platform facing user requirements are clarified.It expounds the WeChat public platform knowledge aggregation concept,objectives and principles,and aggregation service elements.WeChat public platform knowledge aggregation is the personalized knowledge in order to meet user knowledge requirements,through econometric analysis,mathematical statistics,social network analysis,data mining,artificial intelligence methods such as analysis of mining knowledge unit inner link,WeChat public platform complex diverse,huge quantity,disorderly fragments of domain knowledge resource reorganizing and ordering,form a complete knowledge system structure,knowledge aggregation service for subsequent WeChat public platform to provide resource guarantee.By analyzing the motivation and process of knowledge aggregation service of WeChat public platform facing user requirements,this paper proposes the knowledge aggregation service architecture of WeChat public platform oriented user requirements.Second,the construction of user portrait and user requirements analysis of WeChat public platform.Based on the VA1S2 model,group user portraits of WeChat public platform users are constructed from the macro level.Users are divided into three categories:initial participator,resource acquisition,and mature users.The word clouds of various user characteristics are drawn.To build a hierarchical model of users' knowledge needs of WeChat public platform,the process of forming different users' knowledge needs has been analyzed.Based on user portrait and user knowledge requirements hierarchy,a user knowledge requirements model of WeChat public platform is established to highlight the huge gap between the current situation of knowledge service of WeChat public platform and user requirements.(3)The research on knowledge aggregation of WeChat public platform based on tag clustering.This paper proposes an extraction method of knowledge resource tags from WeChat public platform,which integrates Word2vec model and TextRank algorithm.Key words are used as tags to express the theme and key content of knowledge resource content.This paper proposes a WeChat public platform text label clustering method based on the improved Birch clustering algorithm.In the implementation of the algorithm,the K-means algorithm is integrated to select the clustering center,the user knowledge requirements and characteristic factors are comprehensively considered.Finally,an empirical study is carried out on the"cognitive computing" articles published on WeChat public platform.It is found that the clustering results based on the improved BIRCH algorithm proposed in this paper have a reasonable topic distribution,a clear distinction between classes and a small gap in class cluster size,and its effect is better than that based on K-means algorithm,Spectral Clustering algorithm and BIRCH algorithm.(4)The research on knowledge aggregation of WeChat public platform based on abstract generation.A knowledge abstract generation method of WeChat public platform based on improved TextRank algorithm is proposed,and the knowledge abstract generation methods of single text and single domain and multiple text are designed respectively.In the aspect of single text abstract generation,the effect of abstract generation is improved by comprehensively considering the user requirements,sentence position,title similarity and other factors.In the aspect of single-domain multi-text abstract generation,Doc2vec model is used for turning text to vector,subject subdivision of the sentences in the document set is carried out,and MMR algorithm is used for sentence redundancy processing to improve the accuracy of summaries generation.Released to WeChat public platform "cognitive computing"field as an example for empirical study,the study found that using the method of the generated text to better match the user's requirements,to implement user-oriented personalized extract and generate requirements,accurate average recall rate of Precision was significantly superior to other algorithms.And the abstract generated by the algorithm in this paper has a better semantic coherence,which is convenient for readers to understand and further grasp the main idea of the article.(5)The research on innovative knowledge service mode based on knowledge aggregation of WeChat public platform.Based on the framework of knowledge aggregation and service system of WeChat public platform,aiming at knowledge aggregation at different levels,two service modes,namely knowledge recommendation service of WeChat public platform based on knowledge label clustering and knowledge integration service of WeChat public platform based on abstract generation,are constructed.This paper expounds the concepts of two kinds of knowledge service and probes into the connotation of knowledge service elements under different knowledge service modes.(6)The WeChat public platform knowledge aggregation and accurate service ability improvement countermeasures.The countermeasures and suggestions for improving the knowledge aggregation and service ability of WeChat public platform are put forward from three aspects,namely,mining user knowledge requirements,improving the application of knowledge aggregation theory and method,and improving the operation and management of WeChat public platform.This paper introduces the theory and method of knowledge aggregation into the WeChat public platform from the theoretical level,and expands the new research field and new perspective of knowledge aggregation.It enriches the theoretical system of social media platform knowledge service.At the same time,it carries out knowledge topic discovery and automatic abstract generation on the knowledge content published by WeChat official account,and establishes the corresponding knowledge aggregation service system,enriches the theoretical system of new media knowledge service and academic institution knowledge service,and provides theoretical and technical support for academic new media knowledge service.At the practical level,this paper conducts knowledge topic discovery and automatic summaries of knowledge aggregation technology for knowledge resource aggregation of different WeChat official accounts in WeChat public platform,providing technical methods and means for knowledge resource aggregation WeChat public platform.At the same time,it provides reference basis and suggestions for WeChat public platform to carry out innovative knowledge service.