Abstract
Users often have vague or imprecise ideas when searching the e-commerce Web databases such as used cars databases, houses databases etc. and may not be able to formulate queries that accurately express their query intentions. They also would like to obtain the relevant information that meets their needs and preferences closely. In this paper, we present a new approach – QRR (query relaxation and ranking), for relaxing the initial query over e-commerce Web databases in order to provide relevant answer to the user. QRR relaxes the query criteria by adding the most similar values into each query criterion range specified by the initial query, and then the relevant answers which satisfy the relaxed queries could be retrieved. For relevant query results, QRR speculates the importance of each attribute based on the user initial query and assigns the score of each attribute value according to its “desirableness” to the user, and then the relevant answers are ranked according to their satisfaction degree to the user’s needs and preferences. Experimental results demonstrate that QRR can effectively recommend the relevant information to the user and have a high ranking quality as well.
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References
Agrawal, S., Chaudhuri, S., Das, G., Gionis, A.: Automated ranking of database query results. In: Proceedings of CIDR, pp. 171–183 (2003)
Chaudhuri, S., Das, G., Hristidis, V., Weikum, G.: Probabilistic ranking of database query results. In: Proceedings of VLDB, pp. 102–111 (2004)
Cooley, R., Srivastava, J., Mobasher, B.: Web mining: Information and pattern discovery on the World Wide Web. In: Proceedings of the ITCAI, pp. 121–130 (1997)
Hachani, N., Ounelli, H.: A knowledge-based approach for database flexible quering. In: Proceedings of DEXA, pp. 420–424 (2006)
Ichikawa, T., Hirakawa, M.: ARES: A relational database with the capability of performing flexible interpretation of queries. IEEE Transactions on Software Engineering 12(5), 624–634 (1986)
Kieling, W.: Foundations of preferences in database systems. In: Proceedings of VLDB, pp. 311–322 (2002)
Meng, X.F.: Providing flexible queries over web databases. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), vol. 5178, pp. 601–606. Springer, Heidelberg (2008)
Ma, Z.M., Meng, X.F.: A knowledge-based approach for answering database fuzzy queries. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), vol. 5178, pp. 623–630. Springer, Heidelberg (2008)
Rabitti, F.: Retrieval of multimedia documents by imprecise query specification. In: Bancilhon, F., Tsichritzis, D.C., Thanos, C. (eds.) EDBT 1990. LNCS, vol. 416, pp. 202–218. Springer, Heidelberg (1990)
Su, W.F., Wang, J.Y., Huang, Q.: Query result ranking over e-commerce web databases. In: Proceedings of CIKM, pp. 575–584 (2006)
Tahani, V.: A conceptual framework for fuzzy querying processing: a step toward very intelligent databases systems. Information Processing Management 13, 289–303 (1997)
Zadeh, L.A.: Fuzzy Sets. Information and Control 8(3), 338–356 (1965)
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Li, X., Zhang, J., Li, L. (2009). Providing Relevant Answers for Queries over E-Commerce Web Databases. In: Liu, J., Wu, J., Yao, Y., Nishida, T. (eds) Active Media Technology. AMT 2009. Lecture Notes in Computer Science, vol 5820. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04875-3_48
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DOI: https://doi.org/10.1007/978-3-642-04875-3_48
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