A Poset Based Approach for Condition Weighting
Current research in multimedia retrieval (MR) does not satisfactorily mirror research results from psychology revealing a different significance of certain characteristics of a media object to a query in terms of similarity. Although the relevance of user-controlled condition weights has been demonstrated, there is a lack of systems supporting users in setting these weights.
In this work, we present a relevance feedback based approach that supports users to set condition weights in order to retrieve results from the MR system that are consistent with their perception of similarity. Condition weights are learned by a machine based learning algorithm from user preferences based on a partially ordered set.
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- 1.Salton, G., Buckley, C.: Improving Retrieval Performance by Relevance Feedback. Technical report, Ithaca, NY, USA (1988)Google Scholar
- 2.van Rijsbergen, C.J.: Information Retrieval. Butterworths, London (1979)Google Scholar
- 3.Codd, E.F.: A Database Sublanguage Founded on the Relational Calculus. In: SIGFIDET (ed.) ACM SIGFIDET Workshop on Data Description, Access and Control, pp. 35–61 (1971)Google Scholar
- 4.Date, C.J., Darwen, H.: A Guide to the SQL Standard, 3rd edn. Addison-Wesley, Reading (1993)Google Scholar
- 5.Zadeh, L.A.: Fuzzy Sets. Information and Control (8), 338–353 (1965)Google Scholar
- 6.Bruce, V., Green, P.R.: Visual Perception –physiology, psychology and ecology, 2nd edn. reprinted.Lawrence Erlbaum Associates Publishers, Hove and London (1993)Google Scholar
- 7.Selfridge, O.G.: Pandemonium. A paradigm for learning. The mechanics of thought processes (1959)Google Scholar
- 9.Lee, J.H.: Properties of Extended Boolean Models in Information Retrieval. In: SIGIR (ed.) SIGIR 1994: Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 182–190. Springer–Verlag New York, Inc. (1994)Google Scholar
- 12.Schmitt, I.: Weighting in CQQL. Technical Report 4, Cottbus (2007)Google Scholar
- 15.Lowell Workshop: The Lowell Database Research Self Assessment. Technical report (2003)Google Scholar
- 16.Fagin, R., Wimmers, E.L.: A Formula for Incorporating Weights into Scoring Rules. Special Issue of Theoretical Computer Science (239), 309–338 (2000)Google Scholar
- 17.Craik, K.J.W.: The Nature of Explanation. Cambridge University Press, Cambridge (1943)Google Scholar
- 18.Preece, J., Rogers, Y., Sharp, H.: Interaction design: Beyond human–computer interaction. Wiley, New York (2002)Google Scholar
- 19.Shneiderman, B., Plaisant, C.: Designing the user interface: Strategies for effective human–computer interaction, 4th edn. Pearson, Boston (2005)Google Scholar
- 21.Schmitt, I., Schulz, N.: Similarity Relational Calculus and its Reduction to a Similarity Algebra. In: Seipel, D., Turull-Torres, J.M.a. (eds.) FoIKS 2004. LNCS, vol. 2942, pp. 252–272. Springer, Heidelberg (2004)Google Scholar