Text learning for user profiling in e-commerce.
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| Title: | Text learning for user profiling in e-commerce. |
|---|---|
| Authors: | Degemmis, M.1 degemmis@di.uniba.it, Lops, P.1, Ferilli, S.1, Di Mauro, N.1, Basile, T. M. A.1, Semeraro, G.1 |
| Source: | International Journal of Systems Science. 10/20/2006, Vol. 37 Issue 13, p905-918. 14p. 10 Charts, 3 Graphs. |
| Subjects: | Electronic commerce, Machine learning, Artificial intelligence, Consumer profiling, Logic programming, Algorithms, Websites, Online library catalogs |
| Abstract: | Exploring digital collections to find information relevant to a user's interests is a challenging task. Algorithms designed to solve this relevant information problem base their relevance computations on user profiles in which representations of the users' interests are maintained. This article presents a new method, based on the classic Rocchio algorithm for text categorization, able to discover user preferences from the analysis of textual descriptions of items in online catalog of e-commerce Web sites. Experiments have been carried out on several data sets, and results have been compared with those obtained using an inductive logic programming (ILP) approach and a probabilistic one. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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