Effective document clustering for large heterogeneous law firm collections

Jack G. Conrad, Khalid Al-Kofahi, Ying Zhao, George Karypis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Scopus citations


Computational resources for research in legal environments have historically implied remote access to large databases of legal documents such as case law, statutes, law reviews and administrative materials. Today, by contrast, there exists enormous growth in lawyers' electronic work product within these environments, specifically within law firms. Along with this growth has come the need for accelerated knowledge management - -automated assistance in organizing, analyzing, retrieving and presenting this content in a useful and distributed manner.In cases where a relevant legal taxonomy is available, together with representative labeled data, automated text classification tools can be applied. In the absence of these resources, document clustering offers an alternative approach to organizing collections, and an adjunct to search.To explore this approach further, we have conducted sets of successively more complex clustering experiments using primary and secondary law documents as well as actual law firm data. Tests were run to determine the efficiency and effectiveness of a number of essential clustering functions. After examining the performance of traditional or hard clustering applications, we investigate soft clustering (multiple cluster assignments) as well as hierarchical clustering. We show how these latter clustering approaches are effective, in terms of both internal and external quality measures, and useful to legal researchers. Moreover, such techniques can ultimately assist in the automatic or semi-automatic generation of taxonomies for subsequent use by classification programs.

Original languageEnglish (US)
Title of host publication10th International Conference on Artificial Intelligence and Law, Proceedings of the Conference - ICAIL 2005
Number of pages11
StatePublished - 2005
Event10th International Conference on Artificial Intelligence and Law, ICAIL 2005 - Bologna, Italy
Duration: Jun 6 2005Jun 11 2005

Publication series

NameProceedings of the International Conference on Artificial Intelligence and Law


Other10th International Conference on Artificial Intelligence and Law, ICAIL 2005


  • Document clustering
  • Knowledgement management
  • Legal data
  • Taxonomy development


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