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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9560

Title: Update Legal Documents Using Hierarchical Ranking Models and Word Clustering
Authors: Pham, Minh Quang Nhat
Nguyen, Minh Le
Shimazu, Akira
Keywords: Updating Task
Hierarchical Ranking
Word Clustering
Issue Date: 2010-12
Publisher: IOS Press
Volume: 223
Start page: 163
End page: 166
DOI: 10.3233/978-1-60750-682-9-163
Abstract: Our research addresses the task of updating legal documents when newinformation emerges. In this paper, we employ a hierarchical ranking model tothe task of updating legal documents. Word clustering features are incorporatedto the ranking models to exploit semantic relations between words. Experimentalresults on legal data built from the United States Code show that the hierarchicalranking model with word clustering outperforms baseline methods using VectorSpace Model, and word cluster-based features are effective features for the task.
Rights: Reprinted from Frontiers in Artificial Intelligence and Applications, Volume 223, Minh Quang Nhat PHAM, Minh Le NGUYEN and Akira SHIMAZU, Update Legal Documents Using Hierarchical Ranking Models and Word Clustering, pp.163-166, Copyright 2010, with permission from IOS Press.
URI: http://hdl.handle.net/10119/9560
Material Type: author
Appears in Collections:b10-2. 図書 (Book, Book Chapter)

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