Abstract
Document similarity search aims to find documents similar to a query document in a text corpus and return a ranked list of similar documents. Most existing approaches to document similarity search compute similarity scores between the query and the documents based on a retrieval function (e.g. Cosine) and then rank the documents by their similarity scores. In this paper, we proposed a novel retrieval approach based on manifold-ranking of TextTiles to re-rank the initially retrieved documents. The proposed approach can make full use of the intrinsic global manifold structure for the TextTiles of the documents in the re-ranking process. Experimental results demonstrate that the proposed approach can significantly improve the retrieval performances based on different retrieval functions. TextTile is validated to be a better unit than the whole document in the manifold-ranking process.
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Wan, X., Yang, J., Xiao, J. (2006). Document Similarity Search Based on Manifold-Ranking of TextTiles. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_2
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DOI: https://doi.org/10.1007/11880592_2
Publisher Name: Springer, Berlin, Heidelberg
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