Abstract
Query recommender systems give users hints on possible interesting queries relative to their information needs. Most query recommenders are based on static knowledge models built on the basis of past user behaviors recorded in query logs. These models should be periodically updated, or rebuilt from scratch, to keep up with the possible variations in the interests of users. We study query recommender algorithms that generate suggestions on the basis of models that are updated continuously, each time a new query is submitted. We extend two state-of-the-art query recommendation algorithms and evaluate the effects of continuous model updates on their effectiveness and efficiency. Tests conducted on an actual query log show that contrasting model aging by continuously updating the recommendation model is a viable and effective solution.
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References
Baeza-Yates, R., Hurtado, C., Mendoza, M.: Query recommendation using query logs in search engines. In: Lindner, W., Mesiti, M., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds.) EDBT 2004. LNCS, vol. 3268, pp. 588–596. Springer, Heidelberg (2004)
Baeza-Yates, R., Tiberi, A.: Extracting semantic relations from query logs. In: KDD 2007, pp. 76–85. ACM, New York (2007)
Baraglia, R., Castillo, C., Donato, D., Nardini, F.M., Perego, R., Silvestri, F.: The effects of time on query flow graph-based models for query suggestion. In: Proc. RIAO 2010 (2010)
Beeferman, D., Berger, A.: Agglomerative clustering of a search engine query log. In: Proc. KDD 2000, pp. 407–416. ACM, New York (2000)
Boldi, P., Bonchi, F., Castillo, C., Donato, D., Gionis, A., Vigna, S.: The query-flow graph: model and applications. In: Proc. CIKM 2008, pp. 609–618 (2008)
Boldi, P., Bonchi, F., Castillo, C., Donato, D., Vigna, S.: Query suggestions using query-flow graphs. In: Proc. WSCD 2009, pp. 56–63. ACM, New York (2009)
Boldi, P., Bonchi, F., Castillo, C., Vigna, S.: From ’dango’ to ’japanese cakes’: Query reformulation models and patterns. In: Proc. WI 2009. IEEE CS, Los Alamitos (2009)
Cao, H., Jiang, D., Pei, J., He, Q., Liao, Z., Chen, E., Li, H.: Context-aware query suggestion by mining click-through and session data. In: Proc. KDD 2008, pp. 875–883 (2008)
Cayci, A., Sumengen, S., Turkay, C., Balcisoy, S., Saygin, Y.: Temporal dynamics of user interests in web search queries. ICAINAW 0, 762–767 (2009)
Fonseca, B.M., Golgher, P., Pôssas, B., Ribeiro-Neto, B., Ziviani, N.: Concept-based interactive query expansion. In: Proc. CIKM 2005. ACM, New York (2005)
Fonseca, B.M., Golgher, P.B., de Moura, E.S., Ziviani, N.: Using association rules to discover search engines related queries. In: LA-WEB 2003. IEEE CS, Los Alamitos (2003)
Kleinberg, J.: Bursty and hierarchical structure in streams. In: Proc. KDD 2002. ACM, New York (2002)
Muthukrishnan, S.: Data streams: algorithms and applications. Found. Trends Theor. Comput. Sci. 1(2), 117–236 (2005)
Pass, G., Chowdhury, A., Torgeson, C.: A picture of search. In: Proc. INFOSCALE 2006. ACM, New York (2006)
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Broccolo, D., Frieder, O., Nardini, F.M., Perego, R., Silvestri, F. (2010). Incremental Algorithms for Effective and Efficient Query Recommendation. In: Chavez, E., Lonardi, S. (eds) String Processing and Information Retrieval. SPIRE 2010. Lecture Notes in Computer Science, vol 6393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16321-0_2
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DOI: https://doi.org/10.1007/978-3-642-16321-0_2
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