Abstract
Given two stories, Story Link Detection System identifies whether they are discussing the same event. Standard approach in link detection system is to use cosine similarity measure to find whether the two documents are linked. Many researchers applied query expansion technique successfully in link detection system, where models are built from the relevant documents retrieved from the collection using query expansion. In this approach, success depends on the quality of the information retrieval system. In the current research, we propose a new information retrieval system for query expansion that uses intra-cluster similarity of the retrieved documents in addition to the similarity with respect to the query document. Our technique enhances the quality of the retrieval system thus improving the performance of the Link Detection System. Combining this improved IR with our Cohesion Model provides excellent result in link detection. Experimental results confirm the effect of the improved retrieval system in query expansion technique.
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Lakshmi, K., Mukherjee, S. (2007). Improved IR in Cohesion Model for Link Detection System. In: Perner, P. (eds) Advances in Data Mining. Theoretical Aspects and Applications. ICDM 2007. Lecture Notes in Computer Science(), vol 4597. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73435-2_12
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DOI: https://doi.org/10.1007/978-3-540-73435-2_12
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