| With the advent of big data and mobile Internet era,the traditional way of searching and acquiring knowledge based on keyword search cannot satisfy people's needs well.The rapid development of the Internet brings the expansion of information,fragmentation and redundancy issues such as acceleration of the user for the vertical,precise information pursuit,more and more users tend to pay less time and energy cost of acquiring information and knowledge more professional and authoritative,the urgent need of a new type of search and access to knowledge.It is in this big environment that the social question and answer community came into being.The Social Question& Answer Community combines social and question answers,the introduction of social networking to the production,dissemination and sharing of knowledge,meeting the user's precision,vertical and personalized knowledge needs,helping users to acquire and use knowledge efficiently,promoting the flow and interaction of knowledge,rapid development has become an important channel for Internet users to acquire knowledge.However,With the rapid growth of knowledge resources in community questions and answers,the phenomenon of "information overload and lack of knowledge" has emerged.Users spend a lot of time and energy cost in knowledge search,screening and knowledge utilization,making the content and way of knowledge service in existing The Social Question& Answer Community hard to meet users' knowledge needs.At the same time,there are also problems of poor quality of the answer,a large number of useful knowledge,and difficult to be found and used.Therefore,how to optimize and innovate the knowledge service model,implementing effective management organization and mining for users to generate answers,providing better knowledge service for users has become an important problem in the development of The Social Question& Answer Community.In view of this,this paper introduces the theory and concept of knowledge aggregation to the Social Question& Answer Community knowledge service.From the perspective of user oriented knowledge demand,analyzes the community knowledge flow and the needs of user knowledge in the Social Question& Answer Community,putting forward the community knowledge and answer community knowledge service system based on knowledge aggregation,discussing the problem of user generated answer quality evaluation,designs 3 kinds of user generated answers knowledge aggregation method and the corresponding knowledge service mode,and finally puts forward the strategy to promote user answering knowledge aggregation and service ability in Social Question& Answer Community.The main work and conclusion of this paper are as follows:Firstly,it explores the knowledge flow and user knowledge needs of the socialized question and answer community.First,it analyzes the characteristics,ways and processes of the community knowledge and answer community knowledge flow,and analyzes the rules of knowledge flow for the follow-up research.And then analyzes the causes,characteristics and level of social Q & A community user knowledge requirement,reference Cohen and Taylor's hierarchy of needs theory into the objective state of knowledge demand,expression level of consciousness knowledge requirement and knowledge requirement,the eclectic knowledge needs,tailored knowledge needs 5 levels,considering that the requirements of user knowledge are characterized by diversity and integration,randomness and scenario,integration and precision,and dynamic continuity.Finally,we analyze the causes and directions of the dynamic evolution of user knowledge needs.We use the set theory to analyze the dynamic evolution process of users' knowledge needs in 2 contexts of interaction and browsing recommendation.Secondly,putting forward the Social Question& Answer Community knowledge service system based on knowledge aggregation is put forward.First of all,the analysis of the current social question and answer community status and future development trend,outlines the objectives and principles of user generated knowledge aggregation,knowledge aggregation theory into Social Question& Answer Community knowledge service,based on the analysis of knowledge aggregation socialization answers community knowledge service factor,the power and the process,and the corresponding knowledge service model.Finally build a Social Question& Answer Community knowledge service system based on the framework of knowledge aggregation society,including resources layer,processing layer,aggregation layer,service layer and service interface layer,wherein the knowledge aggregation layer is the key layer,and analyzes the function and role of each layer.Third,this paper puts forward the quality evaluation method of Social Question& Answer Community users.First of all,through the literature review and empirical analysis,we have constructed the answer quality evaluation index system which contains 5 dimensions and 16 indicators,including the answer text characteristics,respondent characteristics,timeliness,user characteristics and social emotions.Then the problem of quality evaluation of user's production answer is considered as a typical problem of machine learning classification,and propose an evaluation method based on GA-BP Neural Network.Fourth,Social Question& Answer Community users generate answer knowledge aggregation and service research based on label co occurrence.In order to help users obtain knowledge from the answers efficiently,improve the efficiency of knowledge search and acquisition,providing knowledge navigation and knowledge theme service for users.First,the key phrase in the answer is extracted by phrase matching,and the Text Rank algorithm is used to extract the key phrase in the front answer text to generate the label.Then,it is considered that the generation of answer labels can represent the key knowledge contents and ideas of the answer,and DPCA algorithm is applied to cluster analysis of answer labels to achieve user production knowledge aggregation.Finally,a Social Question& Answer Community knowledge navigation service based on answer label generation and a Social Question& Answer Community knowledge topic discovery service based on answer label clustering are proposed.Fifth,the social question answer community users generate answer knowledge aggregation and service research based on the improved association rules.In order to solve the problem of information overload generated by users in Social Question& Answer Community,mining association relations between knowledge units,realizing user to generate answers related knowledge aggregation,providing users with personalized knowledge recommendation service.We optimize and improve the Apriori algorithm,and design a user generated answer relevance knowledge aggregation method based on improved Apriori algorithm.Finally,Social Question& Answer Community knowledge recommendation service based on the aggregation of answer related knowledge is proposed.Sixth,Social Question& Answer Community users generate answer knowledge aggregation and services based on the answer summary generation.In order to satisfy users' needs for knowledge summarization in Social Question& Answer Community,we need to reduce the cost of answers,search and search,and improve the efficiency of knowledge acquisition and user experience.First,we studied the problem classification of Social Question& Answer Community,and proposed a sentence similarity computing method which integrates word2 vec and multi features to achieve short text sentence similarity computation.Then,an answer summary generation method based on improved Text Rank and MMR algorithm is proposed for the concept class problem;An answer summary generation method based on topic clustering is proposed in view of the problem of opinion consulting;In view of the problem of opinion evaluation,a method of generating an answer summary of the emotional polarity of a sentence is proposed.The validity and rationality of the method of generating the summary of the answers,which know the website as the object of application and the application analysis,is selected.Finally,a Social Question& Answer Community knowledge fusion service based on the generation of answer summary is proposed.From the theoretical level,this paper introduces the theory and concept of knowledge aggregation to the community knowledge service field of question and answer community,the basic theories,such as service concept,service mode,method,value goal and so on,have given new connotations to the Social Question& Answer Community knowledge service.It enriches the theoretical system of knowledge management and service in the social question and answer community,and extends the application field and scope of the theory of knowledge aggregation.It also provides more methods and technical support for user generated answer knowledge aggregation,enriching the theoretical system of knowledge aggregation,and the theoretical system of knowledge mining and organization method in Social Question& Answer Community,it provides technical and method support for users to generate and manage the answer knowledge organization and management,it can be effectively applied to guide users to generate answer knowledge integration organization and management,and improve the ability and quality of the community knowledge and answer community knowledge service,it has a strong application value to solve the practical problem of Social Question& Answer Community knowledge service. |
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