Abstract
Relaxation is a cooperative method to provide informative answers to failing queries of user. The combination of deductive generalization operators in a certain order can avoid unnecessary generalization of duplicate queries. However, it is not expected to return all generalized queries to the user because the theoretical search space exponentially increases with the number of literals of the original query. This paper identifies the minimal generalization in relaxation of conjunctive queries and analyses its properties. The minimal generalization has improved the cooperative behavior of a query answering system to find related information to the user without relaxing all generalized queries. The generalization operators are ordered in relaxation based on its properties. Moreover, it provides a solution to deal with the problem of overgeneralization that leads to queries far from the user’s original intent. The algorithm for finding all minimal generalized queries is proposed based on keeping the fixed order when applying these generalization operators.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Inoue, K., Wiese, L.: Generalizing Conjunctive Queries for Informative Answers. In: Christiansen, H., De Tré, G., Yazici, A., Zadrozny, S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2011. LNCS, vol. 7022, pp. 1–12. Springer, Heidelberg (2011)
Gaasterland, T., Godfrey, P., Minker, J.: Relaxation as a platform for cooperative answering. Journal of Intelligent Information Systems (JIIS) 1(3/4), 293–321 (1992)
Motro, A.: Query Generalization: A method for interpreting null answers. In: Expert Database Workshop, pp. 597–616 (1984)
Godfrey, P.: Minimization in cooperative response to failing database queries. International Journal of Cooperative Information Systems (IJCS) 6(2), 95–149 (1997)
McSherry, D.: Maximally Successful Relaxations of Unsuccessful Queries. In: Proceeding of the 15th Conference on Artificial Intelligence and Cognitive Science, pp. 127–136 (2004)
Jannach, D.: Techniques for Fast Query Relaxation in Content-Based Recommender Systems. In: Freksa, C., Kohlhase, M., Schill, K. (eds.) KI 2006. LNCS (LNAI), vol. 4314, pp. 49–63. Springer, Heidelberg (2007)
Gassterland, T.: Cooperative Answering through Controlled Query Relaxation. Journal IEEE Expert: Intelligent Systems and Their Applications 12(5), 48–59 (1997)
Chu, W.W., Yang, H., Chiang, K., Minock, M., Chow, G., Larson, C.: Cobase: A scalable and extensible cooperative information system. J. Intelligent Information System 6(2/3), 223–259 (1996)
Motro, A.: Flex: A tolerant and cooperative user interface to database. IEEE Transactions on Knowledge & Data Engineering 2(2), 231–246 (1990)
Godfrey, P., Minker, J., Novik, L.: An Architecture for a Cooperative Database System. In: Risch, T., Litwin, W. (eds.) ADB 1994. LNCS, vol. 819, pp. 3–24. Springer, Heidelberg (1994)
Nabeshima, H., Iwanuma, K., Inoue, K., Ray, O.: SOLAR: An automated deduction system for consequence finding. AI Communications 23(2-3), 182–203 (2010)
McSherry, D.: Retrieval Failure and Recovery in Recommender Systems. Journal Artificial Intelligence Review 24(3-4), 319–338 (2005)
Shin, M.K., Huh, S.Y., Lee, W.: Providing ranked cooperative query answers using the metricized knowledge abstraction hierarchy. Expert Systems with Applications 32, 469–484 (2007)
Sakama, C., Inoue, K.: Negotiation by abduction and relaxation. In: AAMAS 2007, IFAAMAS, pp. 1010–1025 (2007)
Sá, S., Alcântara, J.: Abduction-Based Search for Cooperative Answers. In: Leite, J., Torroni, P., Ågotnes, T., Boella, G., van der Torre, L. (eds.) CLIMA XII 2011. LNCS, vol. 6814, pp. 208–224. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pham, TL., Inoue, K. (2012). Minimal Generalization for Conjunctive Queries. In: Sombattheera, C., Loi, N.K., Wankar, R., Quan, T. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2012. Lecture Notes in Computer Science(), vol 7694. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35455-7_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-35455-7_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35454-0
Online ISBN: 978-3-642-35455-7
eBook Packages: Computer ScienceComputer Science (R0)