Using Text Segmentation to Enhance the Cluster Hypothesis

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. Ne...

• Type: Conference
• Year: 2008
• Where: AIMSA
• Authors: Sylvain Lamprier, Tassadit Amghar, Bernard Levrat, Frédéric Saubion
• Keywords: AIMSA 2008, Artificial Intelligence, Clustering Process, Documents, Information Retrieval