Maria Chowdhury

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In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal numbers and polynomials for capturing natural preferences in aggregating opinions of trusted users. We use these opinions to “help” users who are similar to an active user to come(More)
In this paper, we propose a preference framework for information retrieval in which the user and the system administrator are enabled to express preference annotations on search keywords and document elements, respectively. Our framework is flexible and allows expressing preferences such as “A is infinitely more preferred than B,” which we capture by using(More)
Techniques to evaluate XML queries with multiple keywords having fixed relations, such as conjunction, disjunction, ancestor-descendant, and preceding-following, have already been developed. However, an English phrase with a large number of keywords cannot be mapped only with the above keyword relations. A new method to evaluate such natural phrase as the(More)
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