Update Legal Documents Using Hierarchical Ranking Models and Word Clustering

Material type: 図書

Author: Pham, Minh Quang Nhatほか

Publisher: IOS Press

Publication date: 2010-12

Material Format: Digital

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Note (General)：: Our research addresses the task of updating legal documents when newinformation emerges. In this paper, we employ a hierarchical ranking model tothe t...

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Frontiers in Artificial Intelligence and Applications

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Material Type: 図書
Title: Update Legal Documents Using Hierarchical Ranking Models and Word Clustering
Author/Editor: Pham, Minh Quang Nhat
Nguyen, Minh Le
Shimazu, Akira
Author Heading: Pham, Minh Quang Nhat
Nguyen, Minh Le
Shimazu, Akira
Publication, Distribution, etc.: IOS Press
Publication Date: 2010-12
Publication Date (W3CDTF): 2010-12
No. or year of volume/issue: 223
Volume: 223
Pages: 163-166
Text Language Code: eng
Subject Heading: Updating Task
Hierarchical Ranking
Word Clustering
Target Audience: 一般
Note (General): 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.
Legal Knowledge and Information Systems - JURIX 2010: The Twenty-Third Annual Conference Edited by Radboud G.F. Winkels
identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/9560
Access Restrictions: 限定公開
Rights (production): 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.
Related Material: Frontiers in Artificial Intelligence and Applications
Related Material (DOI): 10.3233/978-1-60750-682-9-163
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 北陸先端科学技術大学院大学 : JAIST学術研究成果リポジトリ