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Communication dans un congrès

Using Text Segmentation to Enhance the Cluster Hypothesis

Abstract :

An alternative way to tackle Information Retrieval, called Passage Retrieval, considers text fragments independently rather than assessing global relevance of documents. In such a context, the fact that relevant information is surrounded by parts of text deviating from the interesting topic does not penalize the document. In this paper, we propose to study the impact of the consideration of these text fragments on a document clustering process. The use of clustering in the field of Information Retrieval is mainly supported by the cluster hypothesis which states that relevant documents tend to be more similar one to each other than to non-relevant documents and hence a clustering process is likely to gather them. Previous experiments have shown that clustering the first retrieved documents as response to a user’s query allows the Information Retrieval systems to improve their effectiveness. In the clustering process used in these studies, documents have been considered globally. Nevertheless, the assumption stating that a document can refer to more than one topic/concept may have also impacts on the document clustering process. Considering passages of the retrieved documents separately may allow to create more representative clusters of the addressed topics. Different approaches have been assessed and results show that using text fragments in the clustering process may turn out to be actually relevant.

Type de document :
Communication dans un congrès
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Contributeur : Okina Univ Angers Connectez-vous pour contacter le contributeur
Soumis le : mardi 21 septembre 2021 - 14:34:57
Dernière modification le : mercredi 20 octobre 2021 - 03:19:09

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Sylvain Lamprier, Tassadit Amghar, Bernard Levrat, Frédéric Saubion. Using Text Segmentation to Enhance the Cluster Hypothesis. 13th International Conference, AIMSA 2008, 2008, Varna, Bulgaria. pp.69 - 82, ⟨10.1007/978-3-540-85776-1_7⟩. ⟨hal-03350624⟩



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