Research On The Method Of Question Responders Recommendation In Online Q&A Community

With the continuous development of Web2.0 and the coming of knowledge economy,the knowledge-based community of social question and answer class is favored by more and more users.The online Q&A community,such as Quora,knowledge network and fruit shell network,has gathered a large number of users in a short time,and the momentum of development is swift and violent.However,it is undeniable that the community in the process of development in the process of the gradual emergence of a variety of problems,mainly as follows:1.with the open registration of the community and the increasing demand for the user's knowledge,the accumulation of the content of the user is accumulating,and a large number of problems in the community are unsolved.It is embodied in the online question and answer community that a large number of questions and answers will be generated every day,and the problem is really rarely solved.According to incomplete statistics,there are more than thirty thousand problems waiting to be solved under a single topic[game]known to the community;2.the responders of the online Q&A community invite more mechanisms to mobilize the users.Enthusiasm and neglect of factors such as user's ability and will are not effective in finding effective question respondents.3.,most of the respondents expect to invite respondents who can share knowledge freely and provide high quality answers to help themselves solve problems in time.Based on this research background,first of all,based on literature research,this paper has combed the related research on Knowledge Synergy,expert discovery and problem recommendation and the question of recommender of the virtual community.Secondly,the users of the online Q&A community use the user recommendation theory to focus on the image and use the user recommendation theory.The online Q&A community users recommend measurement dimension and its measurement index,analyze and model the problem responder recommendation method in the online Q&A community;then,verify the effectiveness of the proposed method by knowing the real user data of the community and compare the results with the recommended results of the community problem responders.Finally,based on the results of experiments and analysis,the main findings and corresponding managerial implications are presented.In this paper,the following methods and models are used to study the recommender methods of online Q&A community questions:(1)the use of the hidden Markov probability transfer model can well construct the measurement model of the willingness of user knowledge contribution;(2)the use of polynomial distribution model and cosine similarity to construct the user's interest and specialty model(3)using statistical analysis method to build user activity model;(4)using linear combination method to build online question answering community responder recommendation model.The results show that the effective question responder can be found by taking into account the users' willingness to contribute to knowledge contribution,user interest and expertise,and user activity.The research on question answering method of online question answering community has important guiding significance for communities and users to find effective and effective question respondents.In the study of the two dimensions of user's knowledge contribution and user activity and its related theories and methods,the research perspective and research method recommended by users in virtual communities are expanded to a certain extent,and the theories and methods of user recognition and recommendation are further enriched.It has some guiding significance for designers,operators and participants in online Q&A community.