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Adrian CHIFU

Publication type: Journal Papers

Whether or not word sense disambiguation (WSD) can improve information retrieval (IR) results represents a topic that has been intensely debated over the years, with many inconclusive or contradictory conclusions. The most rarely used type of WSD for this task is the unsupervised one, although it has been proven to be beneficial at a large […]

Comments Off on Feature Selection for Spectral Clustering: to Help or Not to Help Spectral Clustering when Performing Sense Discrimination for IR?

Publication type: Journal Papers

Search engines are based on models to index documents, match queries and documents and rank documents. Research in Information Retrieval (IR) aims at defining these models and their parameters in order to optimize the results. Using benchmark collections, it has been shown that there is not a best system configura- tion that works for any […]

Comments Off on Statistical Analysis to Establish the Importance of Information Retrieval Parameters

Publication type: Journal Papers

Word sense ambiguity has been identified as a cause of poor precision in information retrieval (IR) systems. Word sense disambiguation and discrimination methods have been defined to help systems choose which documents should be retrieved in relation to an ambiguous query. However, the only approaches that show a genuine benefit for word sense discrimination or […]

Comments Off on Word Sense Discrimination in Information Retrieval: A Spectral Clustering-based Approach

Publication type: Journal Papers

Success in Information Retrieval (IR) depends on many variables. Several interdisciplinary approaches try to improve the quality of the results obtained by an IR system. In this paper we propose a new way of using word sense disambiguation (WSD) in IR. The method we develop is based on Naïve Bayes classification and can be used […]

Comments Off on Word Sense Disambiguation to Improve Precision for Ambiguous Queries