45 research outputs found
A comparative evaluation of name-matching algorithms
Name matching—recognizing when two different strings are likely to denote the same entity—is an important task in many legal information systems, such as case-management systems. The naming conventions peculiar to legal cases limit the effectiveness of generic approximate string-matching algorithms in this task. This paper proposes a three-stage framework for name matching, identifies how each stage in the framework addresses the naming variations that typically arise in legal cases, describes several alternative approaches to each stage, and evaluates the performance of various combinations of the alternatives on a representative collection of names drawn from a United States District Court case management system. The best tradeoff between accuracy and efficiency in this collection was achieved by algorithms that standardize capitalization, spacing, and punctuation; filter redundant terms; index using an abstraction function that is both order-insensitive and tolerant of small numbers of omissions or additions; and compare names in a symmetrical, word-by-word fashion. 1
Active case-based reasoning for lessons delivery systems
Paper presented at The 13th International Florida Artificial Intelligence Research Society Conference, FLAIRS 1999, Menlo Park, FL: pp. 170-174.Exploiting lessons learned is a key knowledge management
(KM) task. Currently, most lessons learned systems are
passive, stand-alone systems. In contrast, practical KM
solutions should be active, interjecting relevant information
during decision-making. We introduce an architecture for
active lessons delivery systems, an instantiation of it that
serves as a monitor, and illustrate it in the context of the
conversational case-based plan authoring system HICAP
(Muñoz-Avila et al., 1999). When users interact with
HICAP, updating its domain objects, this monitor accesses a
repository of lessons learned and alerts the user to the
ramifications of the most relevant past experiences. We
demonstrate this in the context of planning noncombatant
evacuation operations