Journal of Computer Science and Technology ›› 2018, Vol. 33 ›› Issue (4): 625-653.doi: 10.1007/s11390-018-1845-0

Special Issue: Surveys; Artificial Intelligence and Pattern Recognition; Data Management and Data Mining

• Special Section on Recommender Systems with Big Data • Previous Articles     Next Articles

A Survey on Expert Recommendation in Community Question Answering

Xianzhi Wang1, Member, ACM, IEEE, Chaoran Huang2, Student Member, ACM, IEEE Lina Yao2, Member, ACM, IEEE, Boualem Benatallah2, Member, IEEE, Manqing Dong2, Student Member, ACM, IEEE   

  1. 1 School of Software, University of Technology Sydney, Sydney, NSW 2007, Australia;
    2 School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia
  • Received:2018-01-21 Revised:2018-06-11 Online:2018-07-05 Published:2018-07-05
  • About author:Xianzhi Wang is a lecturer with School of Software, University of Technology Sydney, Sydney. He received his B.E. degree from Xi'an Jiaotong University, Xi'an, M.E. and Ph.D. degrees from Harbin Institute of Technology, Harbin, all in computer science, in 2007, 2009, and 2014 respectively. His research interests include Internet of Things, data management, machine learning, and services computing. He received ARC Discovery Early Career Researcher Award (DECRA) in 2017 and IBM Ph.D. Fellowship Award in 2013.

Community question answering (CQA) represents the type of Web applications where people can exchange knowledge via asking and answering questions. One significant challenge of most real-world CQA systems is the lack of effective matching between questions and the potential good answerers, which adversely affects the efficient knowledge acquisition and circulation. On the one hand, a requester might experience many low-quality answers without receiving a quality response in a brief time; on the other hand, an answerer might face numerous new questions without being able to identify the questions of interest quickly. Under this situation, expert recommendation emerges as a promising technique to address the above issues. Instead of passively waiting for users to browse and find their questions of interest, an expert recommendation method raises the attention of users to the appropriate questions actively and promptly. The past few years have witnessed considerable efforts that address the expert recommendation problem from different perspectives. These methods all have their issues that need to be resolved before the advantages of expert recommendation can be fully embraced. In this survey, we first present an overview of the research efforts and state-of-the-art techniques for the expert recommendation in CQA. We next summarize and compare the existing methods concerning their advantages and shortcomings, followed by discussing the open issues and future research directions.

Key words: community question answering; expert recommendation; challenge; solution; future direction;

[1] Srba I, Bielikova M. A comprehensive survey and classification of approaches for community question answering. ACM Transactions on the Web, 2016, 10(3):Article No. 18.

[2] Liu Q, Agichtein E, Dror G, Maarek Y, Szpektor I. When web search fails, searchers become askers:Understanding the transition. In Proc. the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2012, pp.801-810.

[3] Guo J, Xu S, Bao S, Yu Y. Tapping on the potential of Q&A community by recommending answer providers. In Proc. the 17th ACM International Conference on Information and Knowledge Management, Oct. 2008, pp.921-930.

[4] Su Q, Pavlov D, Chow J H, Baker W C. Internet-scale collection of human-reviewed data. In Proc. the 16th International Conference on World Wide Web, May 2007, pp.231-240.

[5] Agichtein E, Castillo C, Donato D, Gionis A, Mishne G. Finding high-quality content in social media. In Proc. the International Conference on Web Search and Data Mining, May 2008, pp.183-194.

[6] Li B, King I. Routing questions to appropriate answerers in community question answering services. In Proc. the 19th ACM International Conference on Information and Knowledge Management, Oct. 2010, pp.1585-1588.

[7] Fisher D, Smith M, Welser H T. You are who you talk to:Detecting roles in Usenet newsgroups. In Proc. the 39th Annual Hawaii International Conference on System Sciences, Volume 3, Jan. 2006.

[8] Viégas F B, Smith M. Newsgroup crowds and AuthorLines:Visualizing the activity of individuals in conversational cyberspaces. In Proc. the 37th Annual Hawaii International Conference on System Sciences, Jan. 2004.

[9] Welser H T, Gleave E, Fisher D, Smith M. Visualizing the signatures of social roles in online discussion groups. Journal of Social Structure, 2007, 8(2):1-32.

[10] Anderson A, Huttenlocher D, Kleinberg J, Leskovec J. Discovering value from community activity on focused question answering sites:A case study of Stack Overflow. In Proc. the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2012, pp.850-858.

[11] Adamic L A, Zhang J, Bakshy E, Ackerman M S. Knowledge sharing and Yahoo Answers:Everyone knows something. In Proc. the 17th International Conference on World Wide Web, Apr. 2008, pp.665-674.

[12] Movshovitz-Attias D, Movshovitz-Attias Y, Steenkiste P, Faloutsos C. Analysis of the reputation system and user contributions on a question answering website:StackOverflow. In Proc. the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug. 2013, pp.886-893.

[13] Yimam-Seid D, Kobsa A. Expert-finding systems for organizations:Problem and domain analysis and the DEMOIR approach. Journal of Organizational Computing and Electronic Commerce, 2003, 13(1):1-24.

[14] Zhou Y, Cong G, Cui B, Jensen C S, Yao J. Routing questions to the right users in online communities. In Proc. the 25th IEEE International Conference on Data Engineering, Apr. 2009, pp.700-711.

[15] Qu M, Qiu G, He X, Zhang C, Wu H, Bu J, Chen C. Probabilistic question recommendation for question answering communities. In Proc. the 18th International Conference on World Wide Web, Apr. 2009, pp.1229-1230.

[16] Horowitz D, Kamvar S D. The anatomy of a large-scale social search engine. In Proc. the 19th International Conference on World Wide Web, Apr. 2010, pp.431-440.

[17] Bayati S. Security expert recommender in software engineering. In Proc. the 38th International Conference on Software Engineering Companion, May 2016, pp.719-721.

[18] Rjab A B, Kharoune M, Miklos Z, Martin A. Characterization of experts in crowdsourcing platforms. In Proc. the 4th International Conference on Belief Functions:Theory and Applications, Sept. 2016, pp.97-104.

[19] Baeza-Yates R, Ribeiro-Neto B. Modern Information Retrieval (1st edition). Addison Wesley, 1999.

[20] Balog K, Azzopardi L, de Rijke M. Formal models for expert finding in enterprise corpora. In Proc. the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2006, pp.43-50.

[21] Miller D R, Leek T, Schwartz R M. A hidden Markov model information retrieval system. In Proc. the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1999, pp.214-221.

[22] Zhou G, Liu K, Zhao J. Joint relevance and answer quality learning for question routing in community QA. In Proc. the 21st ACM International Conference on Information and Knowledge Management, Oct. 2012, pp.1492-1496.

[23] Liu X, Croft W B, Koll M. Finding experts in communitybased question-answering services. In Proc. the 14th ACM International Conference on Information and Knowledge Management, Oct. 2005, pp.315-316.

[24] Lavrenko V, Croft W B. Relevance based language models. In Proc. the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sept. 2001, pp.120-127.

[25] Liu X, Croft W B. Cluster-based retrieval using language models. In Proc. the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2004, pp.186-193.

[26] Petkova D, Croft W B. Hierarchical language models for expert finding in enterprise corpora. International Journal on Artificial Intelligence Tools, 2008, 17(1):5-18.

[27] Li B, King I, Lyu M R. Question routing in community question answering:Putting category in its place. In Proc. the 20th ACM International Conference on Information and Knowledge Management, Oct. 2011, pp. 2041-2044.

[28] Zheng X, Hu Z, Xu A, Chen D, Liu K, Li B. Algorithm for recommending answer providers in community-based question answering. Journal of Information Science, 2012, 38(1):3-14.

[29] Zhai C, Lafferty J. A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems, 2004, 22(2):179-214.

[30] Liu M, Liu Y, Yang Q. Predicting best answerers for new questions in community question answering. In Proc. the 11th International Conference on Web-Age Information Management, Jul. 2010, pp.127-138.

[31] Riahi F, Zolaktaf Z, Shafiei M, Milios E. Finding expert users in community question answering. In Proc. the 21st International Conference on World Wide Web, Apr. 2012, pp.791-798.

[32] Hofmann T. Probabilistic latent semantic indexing. In Proc. the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1999, pp.50-57.

[33] Deerwester S, Dumais S T, Furnas G W, Landauer T K, Harshman R. Indexing by latent semantic analysis. Journal of the American Society for Information Science, 1990, 41(6):391-407.

[34] Wu H, Wang Y, Cheng X. Incremental probabilistic latent semantic analysis for automatic question recommendation. In Proc. the ACM Conference on Recommender Systems, Oct. 2008, pp.99-106.

[35] Xu F, Ji Z, Wang B. Dual role model for question recommendation in community question answering. In Proc. the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2012, pp.771-780.

[36] Blei D M, Ng A Y, Jordan M I. Latent Dirichlet allocation. Journal of Machine Learning Research, 2003, 3:993-1022.

[37] Du L, Buntine W, Jin H. A segmented topic model based on the two-parameter Poisson-Dirichlet process. Machine Learning, 2010, 81(1):5-19.

[38] Pitman J, Yor M. The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator. The Annals of Probability, 1997, 25(2):855-900.

[39] Sahu T P, Nagwani N K, Verma S. TagLDA based user persona model to identify topical experts for newly posted questions in community question answering sites. International Journal of Applied Engineering Research, 2016, 11(10):7072-7078.

[40] Tian Y, Kochhar P S, Lim E P, Zhu F, Lo D. Predicting best answerers for new questions:An approach leveraging topic modeling and collaborative voting. In Proc. International Workshops at the International Conference on Social Informatics, Nov. 2013, pp.55-68.

[41] Zhang J, Ackerman M S, Adamic L. Expertise networks in online communities:Structure and algorithms. In Proc. the 16th International Conference on World Wide Web, May 2007, pp.221-230.

[42] Jeon J, Croft W B, Lee J H, Park S. A framework to predict the quality of answers with non-textual features. In Proc. the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2006, pp.228-235.

[43] Borodin A, Roberts G O, Rosenthal J S, Tsaparas P. Link analysis ranking:Algorithms, theory, and experiments. ACM Transactions on Internet Technology, 2005, 5(1):231-297.

[44] Kleinberg J M. Authoritative sources in a hyperlinked environment. Journal of the ACM, 1999, 46(5):604-632.

[45] Jurczyk P, Agichtein E. Discovering authorities in question answer communities by using link analysis. In Proc. the 16th ACM Conference on Information and Knowledge Management, Nov. 2007, pp.919-922.

[46] Jurczyk P, Agichtein E. Hits on question answer portals:Exploration of link analysis for author ranking. In Proc. the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2007, pp.845-846.

[47] Haveliwala T H. Topic-sensitive PageRank. In Proc. the 11th International Conference on World Wide Web, May 2002, pp.517-526.

[48] Choetkiertikul M, Avery D, Dam H K, Tran T, Ghose A. Who will answer my question on Stack Overflow? In Proc. the 24th Australasian Software Engineering Conference, Sept. 2015, pp.155-164.

[49] Lempel R, Moran S. SALSA:The stochastic approach for link-structure analysis. ACM Transactions on Information Systems, 2001, 19(2):131-160.

[50] Cheng T, Yan X, Chang K C C. EntityRank:Searching entities directly and holistically. In Proc. the 33rd International Conference on Very Large Data Bases, Sept. 2007, pp.387-398.

[51] Weng J, Lim E P, Jiang J, He Q. TwitterRank:Finding topic-sensitive influential twitterers. In Proc. the 3rd ACM International Conference on Web Search and Data Mining, Feb. 2010, pp.261-270.

[52] Liu X, Bollen J, Nelson M L, de Sompel H. Co-authorship networks in the digital library research community. Information Processing & Management, 2005, 41(6):1462-1480.

[53] Shahriari M, Parekodi S, Klamma R. Community-aware ranking algorithms for expert identification in questionanswer forums. In Proc. the 15th International Conference on Knowledge Technologies and Data-Driven Business, Oct. 2015, Article No. 8.

[54] Shahriari M, Krott S, Klamma R. Disassortative degree mixing and information diffusion for overlapping community detection in social networks (DMID). In Proc. the 24th International Conference on World Wide Web, May 2015, pp.1369-1374.

[55] Bouguessa M, Dumoulin B, Wang S. Identifying authoritative actors in question-answering forums:The case of Yahoo! Answers. In Proc. the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2008, pp.866-874.

[56] Fagin R, Lotem A, Naor M. Optimal aggregation algorithms for middleware. Journal of Computer and System Sciences, 2003, 66(4):614-656.

[57] Zhu H, Cao H, Xiong H, Chen E, Tian J. Towards expert finding by leveraging relevant categories in authority ranking. In Proc. the 20th ACM International Conference on Information and Knowledge Management, Oct. 2011, pp.2221-2224.

[58] Zhu H, Chen E, Xiong H, Cao H, Tian J. Ranking user authority with relevant knowledge categories for expert finding. World Wide Web, 2014, 17(5):1081-1107.

[59] Liu J, Song Y I, Lin C Y. Competition-based user expertise score estimation. In Proc. the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2011, pp.425-434.

[60] Lai L C, Kao H Y. Question routing by modeling user expertise and activity in CQA services. In Proc. the 26th Annual Conference of the Japanese Society for Artificial Intelligence, Jun. 2012.

[61] Lin Y, Shen H. SmartQ:A question and answer system for supplying high-quality and trustworthy answers. IEEE Transactions on Big Data. doi:10.1109/TBDATA.2017.2735442.

[62] Liu D R, Chen Y H, Kao W C, Wang H W. Integrating expert profile, reputation and link analysis for expert finding in question-answering websites. Information Processing & Management, 2013, 49(1):312-329.

[63] Liu Z, Li K, Qu D. Knowledge graph based question routing for community question answering. In Proc. the 24th International Conference on Neural Information Processing, Nov. 2017, pp.721-730.

[64] Pal A, Konstan J A. Expert identification in community question answering:Exploring question selection bias. In Proc. the 19th ACM International Conference on Information and Knowledge Management, Oct. 2010, pp.1505-1508.

[65] Pal A, Farzan R, Konstan J A, Kraut R E. Early detection of potential experts in question answering communities. In Proc. the 19th International Conference on User Modeling, Adaptation, and Personalization, Jul. 2011, pp.231-242.

[66] Zhou T C, Lyu M R, King I. A classification-based approach to question routing in community question answering. In Proc. the 21st International Conference on World Wide Web, Apr. 2012, pp.783-790.

[67] Ji Z, Wang B. Learning to rank for question routing in community question answering. In Proc. the 22nd ACM International Conference on Information & Knowledge Management, Oct. 2013, pp.2363-2368.

[68] Dijk D, Tsagkias M, de Rijke M. Early detection of topical expertise in community question answering. In Proc. the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2015, pp.995-998.

[69] Le L T, Shah C. Retrieving rising stars in focused community question-answering. In Proc. the 8th Asian Conference on Intelligent Information and Database Systems, Mar. 2016, pp.25-36.

[70] Dror G, Koren Y, Maarek Y, Szpektor I. I want to answer, who has a question? Yahoo! Answers recommender system. In Proc. the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2011, pp.1109-1117.

[71] Pal A, Harper F M, Konstan J A. Exploring question selection bias to identify experts and potential experts in community question answering. ACM Transactions on Information Systems, 2012, 30(2):Article No. 10.

[72] Burel G, Mulholland P, He Y, Alani H. Predicting answering behaviour in online question answering communities. In Proc. the 26th ACM Conference on Hypertext & Social Media, Sept. 2015, pp.201-210.

[73] Burges C J, Ragno R, Le Q V. Learning to rank with nonsmooth cost functions. In Proc. the Neural Information Processing Systems Conference, Dec. 2006, pp.193-200.

[74] Cao Z, Qin T, Liu T Y, Tsai M F, Li H. Learning to rank:From pairwise approach to listwise approach. In Proc. the 24th International Conference on Machine Learning, Jun. 2007, pp.129-136.

[75] Cheng X, Zhu S, Chen G, Su S. Exploiting user feedback for expert finding in community question answering. In Proc. the IEEE International Conference on Data Mining Workshop, Nov. 2015, pp.295-302.

[76] Wang N, Abel M H, Barthés J P, Negre E. An answerer recommender system exploiting collaboration in CQA services. In Proc. the 20th IEEE International Conference on Computer Supported Cooperative Work in Design, May 2016, pp.198-203.

[77] Dom B, Paranjpe D. A Bayesian technique for estimating the credibility of question answerers. In Proc. SIAM International Conference on Data Mining, Apr. 2008, pp.399-409.

[78] Koren Y, Bell R, Volinsky C. Matrix factorization techniques for recommender systems. Computer, 2009, 42(8):30-37.

[79] Cho J H, Li Y, Girju R, Zhai C. Recommending forum posts to designated experts. In Proc. IEEE International Conference on Big Data, Oct. 2015, pp.659-666.

[80] Singh A P, Gordon G J. Relational learning via collective matrix factorization. In Proc. the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2008, pp.650-658.

[81] Yang B, Manandhar S. Tag-based expert recommendation in community question answering. In Proc. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug. 2014, pp.960-963.

[82] Mnih A, Salakhutdinov R R. Probabilistic matrix factorization. In Proc. the 20th International Conference on Neural Information Processing Systems, Dec. 2008, pp.1257-1264.

[83] Zhou G, Liu K, Zhao J. Topical authority identification in community question answering. In Proc. Chinese Conference on Pattern Recognition, Sept. 2012, pp.622-629.

[84] Liu X, Ye S, Li X, Luo Y, Rao Y. ZhihuRrank:A topicsensitive expert finding algorithm in community question answering websites. In Proc. the 14th International Conference on Web-Based Learning, Nov. 2015, pp.165-173.

[85] Yang J, Peng S, Wang L, Wu B. Finding experts in community question answering based on topic-sensitive link analysis. In Proc. the 1st IEEE International Conference on Data Science in Cyberspace, Jun. 2016, pp.54-60.

[86] Rao Y, Xie H, Liu X, Li Q, Wang F L, Wong T L. User authority ranking models for community question answering. Journal of Intelligent & Fuzzy Systems, 2016, 31(5):2533-2542.

[87] Zhao T, Bian N, Li C, Li M. Topic-level expert modeling in community question answering. In Proc. the SIAM International Conference on Data Mining, May 2013, pp.776-784.

[88] Zhou G, Lai S, Liu K, Zhao J. Topic-sensitive probabilistic model for expert finding in question answer communities. In Proc. the 21st ACM International Conference on Information and Knowledge Management, Oct. 2012, pp.1662-1666.

[89] Yang L, Qiu M, Gottipati S, Zhu F, Jiang J, Sun H, Chen Z. CQArank:Jointly model topics and expertise in community question answering. In Proc. the 22nd ACM International Conference on Information & Knowledge Management, Oct. 2013, pp.99-108.

[90] Yan Z, Zhou J. A new approach to answerer recommendation in community question answering services. In Proc. the 34th European Conference on Information Retrieval, Apr. 2012, pp.121-132.

[91] Yin H, Hu Z, Zhou X, Wang H, Zheng K, Nguyen Q V H, Sadiq S. Discovering interpretable geo-social communities for user behavior prediction. In Proc. the 32nd IEEE International Conference on Data Engineering, May 2016, pp.942-953.

[92] Suryanto M A, Lim E P, Sun A, Chiang R H. Quality-aware collaborative question answering:Methods and evaluation. In Proc. the 2nd ACM International Conference on Web Search and Data Mining, Feb. 2009, pp.142-151.

[93] Chang S, Pal A. Routing questions for collaborative answering in community question answering. In Proc. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug. 2013, pp.494-501.

[94] Yeniterzi R, Callan J. Moving from static to dynamic modeling of expertise for question routing in CQA sites. In Proc. the 9th International AAAI Conference on Web and Social Media, May 2015, pp.702-705.

[95] Zhao Z, Zhang L, He X, Ng W. Expert finding for question answering via graph regularized matrix completion. IEEE Transactions on Knowledge and Data Engineering, 2015, 27(4):993-1004.

[96] Zhao Z, Wei F, Zhou M, Ng W. Cold-start expert finding in community question answering via graph regularization. In Proc. the 20th International Conference on Database Systems for Advanced Applications, Apr. 2015, pp.21-38.

[97] Nam K K, Ackerman M S, Adamic L A. Questions in, knowledge in? A study of Naver's question answering community. In Proc. SIGCHI Conference on Human Factors in Computing Systems, Apr. 2009, pp.779-788.

[98] Li X L, Foo C S, Tew K L, Ng S K. Searching for rising stars in bibliography networks. In Proc. the 14th International Conference on Database Systems for Advanced Applications, Apr. 2009, pp.288-292.

[99] Daud A, Abbasi R, Muhammad F. Finding rising stars in social networks. In Proc. the 18th International Conference on Database Systems for Advanced Applications, Apr. 2013, pp.13-24.

[100] Deng H, King I, Lyu M R. Formal models for expert finding on DBLP bibliography data. In Proc. the 8th IEEE International Conference on Data Mining, Dec. 2008, pp.163-172.

[101] Hashemi S H, Neshati M, Beigy H. Expertise retrieval in bibliographic network:A topic dominance learning approach. In Proc. the 22nd ACM International Conference on Information & Knowledge Management, Oct. 2013, pp.1117-1126.

[102] Mimno D, McCallum A. Expertise modeling for matching papers with reviewers. In Proc. the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2007, pp.500-509.

[103] Bagdouri M. Cross-platform question routing for better question answering. In Proc. the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2015, pp.1053-1053.

[104] Richardson M, White R W. Supporting synchronous social Q&A throughout the question lifecycle. In Proc. the 20th International Conference on World Wide Web, Mar. 2011, pp.755-764.

[105] Java A, Kolari P, Finin T, Oates T. Modeling the spread of influence on the blogosphere. In Proc. the 15th International World Wide Web Conference, May 2006, pp.22-26.

[106] Kempe D, Kleinberg J, Tardos É. Maximizing the spread of influence through a social network. In Proc. the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug 2003, pp.137-146.

[107] Pal A, Counts S. Identifying topical authorities in microblogs. In Proc. the 4th ACM International Conference on Web Search and Data Mining, Feb. 2011, pp.45-54.

[108] Campbell C S, Maglio P P, Cozzi A, Dom B. Expertise identification using email communications. In Proc. the 12th International Conference on Information and Knowledge Management, Nov. 2003, pp.528-531.

[109] Dom B, Eiron I, Cozzi A, Zhang Y. Graph-based ranking algorithms for e-mail expertise analysis. In Proc. the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, Jun. 2003, pp.42-48.

[110] Shetty J, Adibi J. Discovering important nodes through graph entropy the case of Enron email database. In Proc. the 3rd International Workshop on Link Discovery, Aug. 2005, pp.74-81.

[111] Mockus A, Herbsleb J D. Expertise browser:A quantitative approach to identifying expertise. In Proc. the 24th International Conference on Software Engineering, May 2002, pp.503-512.

[112] Wei W, Lee J, King I. Measuring credibility of users in an e-learning environment. In Proc. the 16th International Conference on World Wide Web, May 2007, pp.1279-1280.

[113] Fu Y, Xiang R, Liu Y, Zhang M, Ma S. A CDD-based formal model for expert finding. In Proc. the 16th ACM Conference on Information and Knowledge Management, Nov. 2007, pp.881-884.

[114] Balog K, Bogers T, Azzopardi L, de Rijke M, van den Bosch A. Broad expertise retrieval in sparse data environments. In Proc. the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2007, pp.551-558.

[115] Pasca M A, Harabagiu S M. High performance question/answering. In Proc. the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sept. 2001, pp.366-374.

[116] Fang H, Zhai C. Probabilistic models for expert finding. In Proc. the 29th European Conference on Information Retrieval, Apr. 2007, pp.418-430.

[117] Macdonald C, Ounis I. Voting for candidates:Adapting data fusion techniques for an expert search task. In Proc. the 15th ACM International Conference on Information and Knowledge Management, Nov. 2006, pp.387-396.

[118] Liu Y, Bian J, Agichtein E. Predicting information seeker satisfaction in community question answering. In Proc. the 31st International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2008, pp.483-490.

[119] Srba I, Grznar M, Bielikova M. Utilizing non-QA data to improve questions routing for users with low QA activity in CQA. In Proc. the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug. 2015, pp.129-136.

[120] Fagin R, Kumar R, Sivakumar D. Comparing top k lists. SIAM Journal on Discrete Mathematics, 2003, 17(1):134-160.

[121] Herlocker J L, Konstan J A, Terveen L G, Riedl J T. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems, 2004, 22(1):5-53.

[122] Fang L, Huang M, Zhu X. Question routing in community based QA:Incorporating answer quality and answer content. In Proc. the ACM SIGKDD Workshop on Mining Data Semantics, Aug. 2012, Article No. 5.

[123] Sung J, Lee J G, Lee U. Booming up the long tails:Discovering potentially contributive users in community-based question answering services. In Proc. the 7th International AAAI Conference on Weblogs and Social Media, Jul. 2013, pp.602-610.

[124] Yin H, Zhou X, Shao Y, Wang H, Sadiq S. Joint modeling of user check-in behaviors for point-of-interest recommendation. In Proc. the 24th ACM International Conference on Information and Knowledge Management, Oct. 2015, pp.1631-1640.

[125] Yin H, Cui B. Spatio-Temporal Recommendation in Social Media (1st edition). Springer Singapore, 2016.

[126] Liu Q, Agichtein E. Modeling answerer behavior in collaborative question answering systems. In Proc. the 33rd European Conference on Information Retrieval, Apr. 2011, pp.67-79.

[127] Yin H, Zhou X, Cui B, Wang H, Zheng K, Nguyen Q V H. Adapting to user interest drift for POI recommendation. IEEE Transactions on Knowledge and Data Engineering, 2016, 28(10):2566-2581.

[128] Szpektor I, Maarek Y, Pelleg D. When relevance is not enough:Promoting diversity and freshness in personalized question recommendation. In Proc. the 22nd International Conference on World Wide Web, May 2013, pp.1249-1260.

[129] Tong Y, Cao C C, Chen L. TCS:Efficient topic discovery over crowd-oriented service data. In Proc. the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2014, pp.861-870.

[130] Pal A, Chang S, Konstan J A. Evolution of experts in question answering communities. In Proc. the 6th International AAAI Conference on Weblogs and Social Media, Jun. 2012, pp.274-281.

[131] Cai Y, Chakravarthy S. Answer quality prediction in Q/A social networks by leveraging temporal features. International Journal of Next-Generation Computing, 2013, 4(1):127.

[132] Tong Y, She J, Ding B, Wang L, Chen L. Online mobile micro-task allocation in spatial crowdsourcing. In Proc. the 32nd IEEE International Conference on Data Engineering, May 2016, pp.49-60.

[133] Yin H, Chen H, Sun X, Wang H, Wang Y, Nguyen Q V H. SPTF:A scalable probabilistic tensor factorization model for semantic-aware behavior prediction. In Proc. IEEE International Conference on Data Mining, Nov. 2017, pp.585-594.

[134] Yin H, Cui B, Huang Y. Finding a wise group of experts in social networks. In Proc. the 7th International Conference on Advanced Data Mining and Applications, Nov. 2011, pp.381-394.

[135] O'Connor M, Cosley D, Konstan J A, Riedl J. PolyLens:A recommender system for groups of users. In Proc. the 7th European Conference on Computer-Supported Cooperative Work, Sept. 2001, pp.199-218.

[136] Ye M, Liu X, Lee W C. Exploring social influence for recommendation:A generative model approach. In Proc. the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 2012, pp.671-680.

[137] Gorla J, Lathia N, Robertson S, Wang J. Probabilistic group recommendation via information matching. In Proc. the 22nd International Conference on World Wide Web, May 2013, pp.495-504.

[138] Pal A. Metrics and algorithms for routing questions to user communities. ACM Transactions on Information Systems, 2015, 33(3):Article No. 14.

[139] Feng W, Zhu Q, Zhuang J, Yu S. An expert recommendation algorithm based on Pearson correlation coefficient and FP-growth. Cluster Computing. https://doi.org/10.1007/s10586-017-1576-y, June 2018.

[140] Tong Y, Chen L, Zhou Z, Jagadish H V, Shou L, Lv W. SLADE:A smart large-scale task decomposer in crowdsourcing. IEEE Transactions on Knowledge and Data Engineering. doi:10.1109/TKDE.2018.2797962.

[141] Atkinson J, Maurelia A. Redundancy-based trust in question-answering systems. Computer, 2017, 50(1):58-65.

[142] Liu Z, Jansen B J. Predicting potential responders in social Q&A based on non-QA features. In Proc. ACM CHI Conference on Human Factors in Computing Systems, Apr. 2014, pp.2131-2136.

[143] Luo L, Wang F, Zhou M, Pan Y, Chen H. Who have got answers?:Growing the pool of answerers in a smart enterprise social QA system. In Proc. the 19th International Conference on Intelligent User Interfaces, Feb. 2014, p.716.

[144] Rendle S. Factorization machines. In Proc. IEEE International Conference on Data Mining, Dec. 2010, pp.9951000.

[145] Zhou Z H. Ensemble Methods:Foundations and Algorithms (1st edition). CRC Press, 2012.

[146] Friedman J H. Greedy function approximation:A gradient boosting machine. The Annals of Statistics, 2001, 29(5):1189-1232.

[147] Chen T, Guestrin C. XGBoost:A scalable tree boosting system. In Proc. the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2016, pp.785-794.

[148] Yan S, Xu D, Zhang B, Zhang H J, Yang Q, Lin S. Graph embedding and extensions:A general framework for dimensionality reduction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(1):40-51.

[149] Huang C, Yao L, Wang X et al. Expert as a service:Software expert recommendation via knowledge domain embedding in Stack Overflow. In Proc. the 24th IEEE Internation Conference on Web Services, June 2017, pp.317-324.

[150] Yin H, Wang W, Wang H, Chen L, Zhou X. Spatial-aware hierarchical collaborative deep learning for POI recommendation. IEEE Transactions on Knowledge and Data Engineering, 2017, 29(11):2537-2551.

[151] Lin S, Hong W, Wang D, Li T. A survey on expert finding techniques. Journal of Intelligent Information Systems, 2017, 49(2):255-279.

[152] Zheng C, Zhai S, Zhang Z. A deep learning approach for expert identification in question answering communities. arXiv:1711.05350, 2017. https://arxiv.org/abs/1711.05350, Jun. 2018.
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[1] Liu Mingye; Hong Enyu;. Some Covering Problems and Their Solutions in Automatic Logic Synthesis Systems[J]. , 1986, 1(2): 83 -92 .
[2] Chen Shihua;. On the Structure of (Weak) Inverses of an (Weakly) Invertible Finite Automaton[J]. , 1986, 1(3): 92 -100 .
[3] Gao Qingshi; Zhang Xiang; Yang Shufan; Chen Shuqing;. Vector Computer 757[J]. , 1986, 1(3): 1 -14 .
[4] Chen Zhaoxiong; Gao Qingshi;. A Substitution Based Model for the Implementation of PROLOG——The Design and Implementation of LPROLOG[J]. , 1986, 1(4): 17 -26 .
[5] Huang Heyan;. A Parallel Implementation Model of HPARLOG[J]. , 1986, 1(4): 27 -38 .
[6] Min Yinghua; Han Zhide;. A Built-in Test Pattern Generator[J]. , 1986, 1(4): 62 -74 .
[7] Tang Tonggao; Zhao Zhaokeng;. Stack Method in Program Semantics[J]. , 1987, 2(1): 51 -63 .
[8] Min Yinghua;. Easy Test Generation PLAs[J]. , 1987, 2(1): 72 -80 .
[9] Zhu Hong;. Some Mathematical Properties of the Functional Programming Language FP[J]. , 1987, 2(3): 202 -216 .
[10] Li Minghui;. CAD System of Microprogrammed Digital Systems[J]. , 1987, 2(3): 226 -235 .

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