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Hon, \u201cIdentification of ambiguous queries in web search,\u201d Information Processing &amp; Management, vol.45, no.2, pp.216-229, 2009.","DOI":"10.1016\/j.ipm.2008.09.005"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] K. Sp\u00e4rck-Jones, S.E. Robertson, and M. Sanderson, \u201cAmbiguous requests: implications for retrieval tests, systems and theories,\u201d ACM SIGIR Forum, vol.41, no.2, pp.8-17, 2007.","DOI":"10.1145\/1328964.1328965"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] P. Ren, Z. Chen, J. Ma, S. Wang, Z. Zhang, and Z. Ren, \u201cMining and ranking users&apos; intents behind queries,\u201d Information Retrieval Journal, vol.18, no.6, pp.504-529, 2015.","DOI":"10.1007\/s10791-015-9271-1"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] C.-J. Wang, Y.-W. Lin, M.-F. Tsai, and H.-H. Chen, \u201cMining subtopics from different aspects for diversifying search results,\u201d Information retrieval, vol.16, no.4, pp.452-483, 2013.","DOI":"10.1007\/s10791-012-9215-y"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] T.N. Nguyen and N. Kanhabua, \u201cLeveraging dynamic query subtopics for time-aware search result diversification,\u201d in Advances in Information Retrieval, pp.222-234, Springer, 2014.","DOI":"10.1007\/978-3-319-06028-6_19"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] C.L.A. Clarke, M. Kolla, G.V. Cormack, O. Vechtomova, A. Ashkan, S. B\u00fcttcher, and I. MacKinnon, \u201cNovelty and diversity in information retrieval evaluation,\u201d Proc. 31st annual international ACM SIGIR conference on Research and development in information retrieval, pp.659-666, ACM, 2008.","DOI":"10.1145\/1390334.1390446"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] T. Sakai, Z. Dou, T. Yamamoto, Y. Liu, M. Zhang, M.P. Kato, R. Song, and M. Iwata, \u201cSummary of the ntcir-10 intent-2 task: Subtopic mining and search result diversification,\u201d Proc. 36th international ACM SIGIR conference on Research and development in information retrieval, pp.761-764, ACM, 2013.","DOI":"10.1145\/2484028.2484104"},{"key":"8","unstructured":"[8] Y. Liu, R. Song, M. Zhang, Z. Dou, T. Yamamoto, M.P. Kato, H. Ohshima, and K. Zhou, \u201cOverview of the ntcir-11 imine task,\u201d Proc. NTCIR, pp.8-23, 2014."},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor, \u201cFreebase: a collaboratively created graph database for structuring human knowledge,\u201d Proc. 2008 ACM SIGMOD international conference on Management of data, pp.1247-1250, ACM, 2008.","DOI":"10.1145\/1376616.1376746"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] R.L.T. Santos, C. Macdonald, and I. Ounis, \u201cExploiting query reformulations for web search result diversification,\u201d Proc. 19th international conference on World wide web, pp.881-890, ACM, 2010.","DOI":"10.1145\/1772690.1772780"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] Q. Wang, Y. Qian, R. Song, Z. Dou, F. Zhang, T. Sakai, and Q. Zheng, \u201cMining subtopics from text fragments for a web query,\u201d Information retrieval, vol.16, no.4, pp.484-503, 2013.","DOI":"10.1007\/s10791-013-9221-8"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] S. Hu, Z. Dou, X. Wang, T. Sakai, and J.-R. Wen, \u201cSearch result diversification based on hierarchical intents,\u201d Proc. 24th ACM International on Conference on Information and Knowledge Management, pp.63-72, ACM, 2015.","DOI":"10.1145\/2806416.2806455"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] T. Sakai, Z. Dou, T. Yamamoto, Y. Liu, M. Zhang, R. Song, M. Kato, and M. Iwata, \u201cOverview of the ntcir-10 intent-2 task,\u201d Proc. NTCIR-10, pp.94-123, 2013.","DOI":"10.1145\/2484028.2484104"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] J. Carbonell and J. Goldstein, \u201cThe use of mmr, diversity-based reranking for reordering documents and producing summaries,\u201d Proc. 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp.335-336, ACM, 1998.","DOI":"10.1145\/290941.291025"},{"key":"15","unstructured":"[15] T. Yamamoto, Y. Liu, M. Zhang, Z. Dou, K. Zhou, I. Markov, M.P. Kato, H. Ohshima, and S. Fujita, \u201cOverview of the ntcir-12 imine-2 task,\u201d Proc. 12th NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retrieval, Quesiton Answering, And Cross-Lingual Information Access, pp.94-123, 2016."},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] C.L. Clarke, N. Craswell, and I. Soboroff, \u201cOverview of the trec 2009 web track,\u201d Tech. Rep., DTIC Document, 2009.","DOI":"10.6028\/NIST.SP.500-278.web-overview"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] A. Broder, \u201cA taxonomy of web search,\u201d ACM Sigir forum, vol.36, no.2, pp.3-10, 2002.","DOI":"10.1145\/792550.792552"},{"key":"18","unstructured":"[18] B.V. Nguyen and M.Y. Kan, \u201cFunctional faceted web query analysis,\u201d WWW2007: 16th International World Wide Web Conference, 2007."},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] P. Boldi, F. Bonchi, C. Castillo, D. Donato, A. Gionis, and S. Vigna, \u201cThe query-flow graph: model and applications,\u201d Proc. 17th ACM conference on Information and knowledge management, pp.609-618, ACM, 2008.","DOI":"10.1145\/1458082.1458163"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] Z. Zhang and O. Nasraoui, \u201cMining search engine query logs for query recommendation,\u201d Proc. 15th international conference on World Wide Web, pp.1039-1040, 2006.","DOI":"10.1145\/1135777.1136004"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] Q. Mei, D. Zhou, and K. Church, \u201cQuery suggestion using hitting time,\u201d Proc. 17th ACM conference on Information and knowledge management, pp.469-478, ACM, 2008.","DOI":"10.1145\/1458082.1458145"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] Y. Wu, W. Wu, Z. Li, and M. Zhou, \u201cMining query subtopics from questions in community question answering,\u201d AAAI, pp.339-345, 2015.","DOI":"10.1609\/aaai.v29i1.9166"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] J. Hu, G. Wang, F. Lochovsky, J.-T. Sun, and Z. Chen, \u201cUnderstanding user&apos;s query intent with wikipedia,\u201d Proc. 18th international conference on World wide web, pp.471-480, ACM, 2009.","DOI":"10.1145\/1526709.1526773"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[24] F. Radlinski, M. Szummer, and N. Craswell, \u201cInferring query intent from reformulations and clicks,\u201d Proc. 19th international conference on World wide web, pp.1171-1172, ACM, 2010.","DOI":"10.1145\/1772690.1772859"},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] J.G. Moreno, G. Dias, and G. Cleuziou, \u201cQuery log driven web search results clustering,\u201d Proc. 37th international ACM SIGIR conference on Research &amp; development in information retrieval, pp.777-786, ACM, 2014.","DOI":"10.1145\/2600428.2609583"},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] A. Damien, M. Zhang, Y. Liu, and S. Ma, \u201cImprove web search diversification with intent subtopic mining,\u201d in Natural Language Processing and Chinese Computing, pp.322-333, Springer, 2013.","DOI":"10.1007\/978-3-642-41644-6_30"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] S.-J. Kim and J.-H. Lee, \u201cSubtopic mining using simple patterns and hierarchical structure of subtopic candidates from web documents,\u201d Inf. Process. Manage., vol.51, no.6, pp.773-785, Nov. 2015.","DOI":"10.1016\/j.ipm.2015.07.001"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] S.J. Kim, J. Shin, and J.H. Lee, \u201cSubtopic mining based on three-level hierarchical search intentions,\u201d European Conference on Information Retrieval, pp.741-747, 2016.","DOI":"10.1007\/978-3-319-30671-1_62"},{"key":"29","unstructured":"[29] T. Mikolov, I. Sutskever, K. Chen, G.S. Corrado, and J. Dean, \u201cDistributed representations of words and phrases and their compositionality,\u201d Advances in Neural Information Processing Systems, pp.3111-3119, 2013."},{"key":"30","unstructured":"[30] Y. Xue, F. Chen, A. Damien, C. Luo, X. Li, S. Huo, M. Zhang, Y. Liu, and S. Ma, \u201cThuir at ntcir-10 intent-2 task,\u201d Proc. NTCIR, 2013."},{"key":"31","unstructured":"[31] J.G. Moreno and G. Dias, \u201cHultech at the ntcir-10 intent-2 task: Discovering user intents through search results clustering,\u201d Proc. NTCIR, 2013."},{"key":"32","unstructured":"[32] J. Wang, G. Tang, Y. Xia, Q. Zhou, F. Zheng, Q. Hu, S. Na, and Y. Huang, \u201cUnderstanding the query: Thcib and thuis at ntcir-10 intent task,\u201d Proc. NTCIR, 2013."},{"key":"33","unstructured":"[33] S.J. Kim and J.H. Lee, \u201cThe kle&apos;s subtopic mining system for the ntcir-10 intent-2 task,\u201d Proc. NTCIR, 2013."},{"key":"34","unstructured":"[34] M.Z. Ullah, M. Aono, and M.H. Seddiqui, \u201cSem12 at the ntcir-10 intent-2 english subtopic mining subtask,\u201d Proc. NTCIR, 2013."},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] R. Krovetz, \u201cViewing morphology as an inference process,\u201d Proc. 16th annual international ACM SIGIR conference on Research and development in information retrieval, pp.191-202, ACM, 1993.","DOI":"10.1145\/160688.160718"},{"key":"36","doi-asserted-by":"crossref","unstructured":"[36] T.-Y. Liu, \u201cLearning to rank for information retrieval,\u201d Foundations and Trends in Information Retrieval, vol.3, no.3, pp.225-331, 2009.","DOI":"10.1561\/1500000016"},{"key":"37","unstructured":"[37] G. Amati, Probability models for information retrieval based on divergence from randomness, Ph.D. thesis, University of Glasgow, 2003."},{"key":"38","doi-asserted-by":"crossref","unstructured":"[38] S. Robertson and H. Zaragoza, The probabilistic relevance framework: BM25 and beyond, Now Publishers, 2009.","DOI":"10.1561\/1500000019"},{"key":"39","doi-asserted-by":"crossref","unstructured":"[39] J. Lafferty and C. Zhai, \u201cDocument language models, query models, and risk minimization for information retrieval,\u201d Proc. 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp.111-119, ACM, 2001.","DOI":"10.1145\/383952.383970"},{"key":"40","doi-asserted-by":"crossref","unstructured":"[40] C. Zhai and J. Lafferty, \u201cA study of smoothing methods for language models applied to ad hoc information retrieval,\u201d Proc. 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp.334-342, ACM, 2001.","DOI":"10.1145\/383952.384019"},{"key":"41","doi-asserted-by":"crossref","unstructured":"[41] D. Metzler and W.B. Croft, \u201cA markov random field model for term dependencies,\u201d Proc. 28th annual international ACM SIGIR conference on Research and development in information retrieval, pp.472-479, ACM, 2005.","DOI":"10.1145\/1076034.1076115"},{"key":"42","unstructured":"[42] D. Metzler and T. Kanungo, \u201cMachine learned sentence selection strategies for query-biased summarization,\u201d SIGIR Learning to Rank Workshop, pp.40-47, 2008."},{"key":"43","doi-asserted-by":"crossref","unstructured":"[43] G. Salton and C. Buckley, \u201cTerm-weighting approaches in automatic text retrieval,\u201d Information processing &amp; management, vol.24, no.5, pp.513-523, 1988.","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"44","doi-asserted-by":"crossref","unstructured":"[44] M. Bendersky, W.B. Croft, and Y. Diao, \u201cQuality-biased ranking of web documents,\u201d Proc. fourth ACM international conference on Web search and data mining, pp.95-104, ACM, 2011.","DOI":"10.1145\/1935826.1935849"},{"key":"45","doi-asserted-by":"crossref","unstructured":"[45] H. Zou and T. Hastie, \u201cRegularization and variable selection via the elastic net,\u201d Journal of the Royal Statistical Society: Series B(Statistical Methodology), vol.67, no.2, pp.301-320, 2005.","DOI":"10.1111\/j.1467-9868.2005.00503.x"},{"key":"46","doi-asserted-by":"crossref","unstructured":"[46] N.H. Do and K. Yanai, \u201cVisualtextualrank: An extension of visualrank to large-scale video shot extraction exploiting tag co-occurrence,\u201d IEICE Trans. Inf. &amp; Syst., vol.E98-D, no.1, pp.166-172, 2015.","DOI":"10.1587\/transinf.2014EDP7106"},{"key":"47","doi-asserted-by":"crossref","unstructured":"[47] L. Cao, J. Guo, and X. Cheng, \u201cBipartite graph based entity ranking for related entity finding,\u201d 2011 IEEE\/WIC\/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp.130-137, IEEE, 2011.","DOI":"10.1109\/WI-IAT.2011.60"},{"key":"48","doi-asserted-by":"crossref","unstructured":"[48] M.Z. Ullah, M. Aono, and M.H. Seddiqui, \u201cEstimating a ranked list of human genetic diseases by associating phenotype-gene with gene-disease bipartite graphs,\u201d ACM Trans. Intell. Syst. Technol., vol.6, no.4, pp.56:1-56:21, July 2015.","DOI":"10.1145\/2700487"},{"key":"49","doi-asserted-by":"crossref","unstructured":"[49] H. Deng, M.R. Lyu, and I. King, \u201cA generalized co-hits algorithm and its application to bipartite graphs,\u201d Proc. 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD &apos;09, New York, NY, USA, pp.239-248, ACM, 2009.","DOI":"10.1145\/1557019.1557051"},{"key":"50","unstructured":"[50] J. Callan, M. Hoy, C. Yoo, and L. Zhao, \u201cClueweb09 data set,\u201d 2009."},{"key":"51","unstructured":"[51] T. Strohman, D. Metzler, H. Turtle, and W.B. Croft, \u201cIndri: A language model-based search engine for complex queries,\u201d Proc. International Conference on Intelligent Analysis, pp.2-6, Citeseer, 2005."},{"key":"52","unstructured":"[52] T. Sakai, \u201cNtcireval: A generic toolkit for information access evaluation,\u201d Proc. Forum on Information Technology, pp.23-30, 2011."},{"key":"53","doi-asserted-by":"crossref","unstructured":"[53] T. Sakai, \u201cStatistical reform in information retrieval?,\u201d ACM SIGIR Forum, vol.48, no.1, pp.3-12, 2014.","DOI":"10.1145\/2641383.2641385"},{"key":"54","doi-asserted-by":"crossref","unstructured":"[54] R.L.T. Santos, C. Macdonald, and I. 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