Hubs, authorities, and communities
ACM Computing Surveys (CSUR)
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
MAYA: a fast Question-answering system based on a predictive answer indexer
ODQA '01 Proceedings of the workshop on Open-domain question answering - Volume 12
A framework to predict the quality of answers with non-textual features
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Adapting Interaction Analysis to Support Evaluation and Regulation: A Case Study
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
Hits on question answer portals: exploration of link analysis for author ranking
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
On the hierarchicalness of q&a posting networks
Proceedings of the 16th ACM international conference on Supporting group work
Social network analysis of an online dating network
Proceedings of the 5th International Conference on Communities and Technologies
Competition-based networks for expert finding
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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An online question answering (QA) portal provides users a way to socialize and help each other to solve problems. The majority of the online question answer systems use user-feedback to rank users’ answers. This way of ranking is inefficient as it involves ongoing efforts by the users and is subjective. Currently researchers have utilized link analysis of user interactions for this task. However, this is not accurate in some circumstances. A detailed structural analysis of an online QA portal is conducted in this paper. A novel approach based on users’ reputation reflecting the usage patterns is proposed to rank and recommend the user answers. The method is compared with a popular link topology analysis method, HITS. The result of the proposed method is promising.