Abstract
As a representation for multi-documents summarization, a table of indexes in hierarchical structure helps the readers understanding the content and the structure in semantics aspects. It also provides a navigation for the readers to quickly refer to interested information. In this paper, we introduce a framework to generate a hierarchical table of indexes. In which, we apply unsupervised clustering algorithm to create the hierarchical structure, and graph-based ranking method to extract keyphrases and form the indexes. The preliminary result is provided as the illustration for our approach.
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Le, T.T.N., Le Nguyen, M., Shimazu, A. (2012). A Study on Hierarchical Table of Indexes for Multi-documents. In: Isahara, H., Kanzaki, K. (eds) Advances in Natural Language Processing. JapTAL 2012. Lecture Notes in Computer Science(), vol 7614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33983-7_22
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DOI: https://doi.org/10.1007/978-3-642-33983-7_22
Publisher Name: Springer, Berlin, Heidelberg
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