Abstract
Query recommendations help users to formulate better queries and to obtain the desired search results. Users’ clicks on query recommendations contain a great deal of information about search intent, query ambiguity and search performance. We use query recommendation click information contained in search logs to construct a recommendation click graph. A directed edge in the graph connects the prior query and the clicked recommended query. By analyzing the graph, we develop methods for finding ambiguous queries and improving the search results. The experimental results show that our method for finding ambiguous queries is effective, and using recommendation click information can improve the search performance of ambiguous queries.
This work was supported by Natural Science Foundation (60903107, 61073071) and National High Technology Research and Development (863) Program (2011AA01A205) of China.
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References
Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46, 604–632 (1999)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30(1-7), 107–117 (1998); Proceedings of the Seventh International World Wide Web Conference
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web (1998)
Gyöngyi, Z., Garcia-Molina, H., Pedersen, J.: Combating web spam with trustrank. In: Proceedings of the Thirtieth International Conference on Very Large Data Bases, VLDB 2004, vol. 30, pp. 576–587. VLDB Endowment (2004)
Baeza-Yates, R.: Graphs from Search Engine Queries. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds.) SOFSEM 2007. LNCS, vol. 4362, pp. 1–8. Springer, Heidelberg (2007), http://dx.doi.org/10.1007/978-3-540-69507-3_1
Baeza-Yates, R., Tiberi, A.: Extracting semantic relations from query logs. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007, pp. 76–85. ACM, New York (2007)
Boldi, P., Bonchi, F., Castillo, C., Donato, D., Gionis, A., Vigna, S.: The query-flow graph: model and applications. In: Proceedings of CIKM 2008 (2008)
Boldi, P., Bonchi, F., Castillo, C., Donato, D., Vigna, S.: Query suggestions using query-flow graphs. In: Proceedings of the 2009 Workshop on Web Search Click Data, WSCD 2009, pp. 56–63. ACM, New York (2009)
Bai, L., Guo, J., Cheng, X.: Query Recommendation by Modelling the Query-Flow Graph. In: Salem, M.V.M., Shaalan, K., Oroumchian, F., Shakery, A., Khelalfa, H. (eds.) AIRS 2011. LNCS, vol. 7097, pp. 137–146. Springer, Heidelberg (2011), http://dx.doi.org/10.1007/978-3-642-25631-8_13
Zaïane, O.R., Strilets, A.: Finding Similar Queries to Satisfy Searches Based on Query Traces. In: Bruel, J.-M., Bellahsène, Z. (eds.) OOIS 2002. LNCS, vol. 2426, pp. 207–216. Springer, Heidelberg (2002), http://dx.doi.org/10.1007/3-540-46105-1_24
Baeza-Yates, R., Hurtado, C., Mendoza, M.: Query Recommendation Using Query Logs in Search Engines. In: Lindner, W., Fischer, F., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds.) EDBT 2004. LNCS, vol. 3268, pp. 588–596. Springer, Heidelberg (2004), http://dx.doi.org/10.1007/978-3-540-30192-9_58
Yan, X., Guo, J., Cheng, X.: Context-aware query recommendation by learning high-order relation in query logs. In: Proceedings of CIKM 2011 (2011)
Szpektor, I., Gionis, A., Maarek, Y.: Improving recommendation for long-tail queries via templates. In: Proceedings of the 20th International Conference on World Wide Web, WWW 2011, pp. 47–56. ACM, New York (2011)
Ma, H., Yang, H., King, I., Lyu, M.R.: Learning latent semantic relations from clickthrough data for query suggestion. In: Proceeding of CIKM 2008 (2008)
Mei, Q., Zhou, D., Church, K.: Query suggestion using hitting time. In: Proceeding of CIKM 2008 (2008)
Kelly, D., Cushing, A., Dostert, M., Niu, X., Gyllstrom, K.: Effects of popularity and quality on the usage of query suggestions during information search. In: Proceedings of the 28th International Conference on Human Factors in Computing Systems, CHI 2010, pp. 45–54. ACM, New York (2010)
Song, R., Luo, Z., Wen, J.R., Yu, Y., Hon, H.W.: Identifying ambiguous queries in web search. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pp. 1169–1170. ACM, New York (2007)
He, X., Jhala, P.: Regularized query classification using search click information. Pattern Recognition 41(7), 2283–2288 (2008)
Veilumuthu, A., Ramachandran, P.: Intent based clustering of search engine query log. In: Proceedings of the Fifth Annual IEEE International Conference on Automation Science and Engineering, CASE 2009, pp. 647–652. IEEE Press, Piscataway (2009)
Jansen, B.J., Spink, A., Bateman, J., Saracevic, T.: Real life information retrieval: a study of user queries on the web. SIGIR Forum 32, 5–17 (1998)
Fleiss, J.L.: Measuring nominal scale agreement among many raters. Psychological Bulletin 76(5), 378–382 (1971)
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Xue, Y., Liu, Y., Zhang, M., Ma, S., Ru, L. (2012). The Recommendation Click Graph: Properties and Applications. In: Zhou, M., Zhou, G., Zhao, D., Liu, Q., Zou, L. (eds) Natural Language Processing and Chinese Computing. NLPCC 2012. Communications in Computer and Information Science, vol 333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34456-5_26
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DOI: https://doi.org/10.1007/978-3-642-34456-5_26
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