Abstract
Emergent Semantics is a new paradigm for inferring semantic meaning from implicit feedback by a sufficiently large number of users of an object retrieval system. In this paper, we introduce a universal architecture for emergent semantics using a central repository within a multi-user environment, based on solid linguistic theories.
Based on this architecture, we have implemented an information retrieval system supporting keyword queries on standard information retrieval corpora. Contrary to existing query refinement strategies, feedback on the retrieval results is incorporated directly into the actual document representations improving future retrievals.
An evaluation yields higher precision values at the standard recall levels and thus demonstrates the effectiveness of the emergent semantics approach for typical information retrieval problems.
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References
Salton, G., McGill, M.: Introduction to Modern Information Retrieval. McGraw-Hill Book Company, New York (1984)
Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A.: Indexing by Latent Semantic Analysis. Journal of the American Society of Information Science 41(6), 391–407 (1990)
Morris, C.W.: Foundations of the Theory of Signs. Chicago University Press, Chicago (1938)
Jacob, C., Radusch, I., Steglich, S.: Enhancing legacy services through context-enriched sensor data. In: Proceedings of the International Conference on Internet Computing (2006)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)
Salton, G., Lesk, M.E.: Computer evaluation of indexing and text processing. Journal of the ACM 15(1), 8–36 (1968)
Robertson, S.E., Jones, K.S.: Relevance weighting of search terms. Journal of the American Society for Information Science 27(3), 129–146 (1976)
The Apache Software Foundation (2006), http://lucene.apache.org
Shardanand, U., Maes, P.: Social information filtering: algorithms for automating “word of mouth”. In: Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 210–217. ACM Press, New York (1995)
Oard, D.W.: The state of the art in text filtering. User Modeling and User-Adapted Interaction 7(3), 141–178 (1997)
Heflin, J., Hendler, J., Luke, S.: SHOE: A knowledge representation language for internet applications. Technical Report CS-TR-4078 (UMIACS TR-99-71), University of Maryland (1999)
Grosky, W.I., Sreenath, D.V., Fotouhi, F.: Emergent semantics and the multimedia semantic web. SIGMOD Rec. 31(4), 54–58 (2002)
Aberer, K., Cudré-Mauroux, P., Hauswirth, M.: The chatty web: emergent semantics through gossiping. In: Proceedings of the Twelfth International Conference on World Wide Web, pp. 197–206. ACM Press, New York (2003)
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Herschel, S., Heese, R., Bleiholder, J. (2006). An Architecture for Emergent Semantics. In: Roddick, J.F., et al. Advances in Conceptual Modeling - Theory and Practice. ER 2006. Lecture Notes in Computer Science, vol 4231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908883_50
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DOI: https://doi.org/10.1007/11908883_50
Publisher Name: Springer, Berlin, Heidelberg
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