Update Legal Documents Using Hierarchical Ranking Models and Word Clustering

Authors:
Minh Quang Nhat Pham;Minh Le Nguyen;Akira Shimazu
Affiliations:
School of Information Science, Japan Advanced Institute of Science and Technology;School of Information Science, Japan Advanced Institute of Science and Technology;School of Information Science, Japan Advanced Institute of Science and Technology
Venue:
Proceedings of the 2010 conference on Legal Knowledge and Information Systems: JURIX 2010: The Twenty-Third Annual Conference
Year:
2010

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Abstract

Our research addresses the task of updating legal documents when new information emerges. In this paper, we employ a hierarchical ranking model to the task of updating legal documents. Word clustering features are incorporated to the ranking models to exploit semantic relations between words. Experimental results on legal data built from the United States Code show that the hierarchical ranking model with word clustering outperforms baseline methods using Vector Space Model, and word cluster-based features are effective features for the task.