Similarity of Legal Cases: From Temporal Relations of Affairs

Authors: Tojo, S.1; Nitta, K.2

Source: Artificial Intelligence and Law, Volume 5, Numbers 1-2, March 1997 , pp. 161-176(16)

Publisher: Springer

Buy & download fulltext article:

OR

Price: $47.00 plus tax (Refund Policy)

Abstract:

Case-based reasoning has played an important role in legal reasoning systems. As one criteria for similarity of cases, temporal relations among affairs in legal cases should be compared. Thus far in many legal reasoning systems, cases have been described as sequences of pointwise events, or at best, simple time intervals, and they have been related by predicates such as `before', `after', `while', and so on. However, such relations may depend on each implementer's personal view, and also require much labor to write down by hand. In this paper, we first propose a classification of affair types by their temporal features, and according to those types, we propose several assumption rules that prescribe the temporal relations between affair types. The temporal relations are automatically generated by these rules. Thereafter, we discuss how these temporal relations work in the comparison of similarity of cases. In the process of comparison, inadequate temporal relations need to be amended. For this purpose, we introduce revision rules, that refute the results of assumption rules.

Keywords: aspect; case-based reasoning; event calculus; similarity; temporal relations

Document Type: Regular Paper

Affiliations: 1: Japan Advanced Institute of Science and Technology, Tatsunokuchi, Ishikawa 923-12, Japan (E-mail: tojo@jaist.ac.jp) 2: Electrotechnical Laboratory, 1-1-4 Umezono, Tsukuba, Ibaragi 305, Japan (E-mail: nitta@etl.go.jp)

Publication date: March 1, 1997

Related content

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page