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The Use of Text Mining Techniques in Electronic Discovery for Legal Matters

The Use of Text Mining Techniques in Electronic Discovery for Legal Matters

Michael W. Berry, Reed Esau, Bruce Kiefer
Copyright: © 2012 |Pages: 17
ISBN13: 9781466603301|ISBN10: 1466603305|EISBN13: 9781466603318
DOI: 10.4018/978-1-4666-0330-1.ch008
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MLA

Berry, Michael W., et al. "The Use of Text Mining Techniques in Electronic Discovery for Legal Matters." Next Generation Search Engines: Advanced Models for Information Retrieval, edited by Christophe Jouis, et al., IGI Global, 2012, pp. 174-190. https://doi.org/10.4018/978-1-4666-0330-1.ch008

APA

Berry, M. W., Esau, R., & Kiefer, B. (2012). The Use of Text Mining Techniques in Electronic Discovery for Legal Matters. In C. Jouis, I. Biskri, J. Ganascia, & M. Roux (Eds.), Next Generation Search Engines: Advanced Models for Information Retrieval (pp. 174-190). IGI Global. https://doi.org/10.4018/978-1-4666-0330-1.ch008

Chicago

Berry, Michael W., Reed Esau, and Bruce Kiefer. "The Use of Text Mining Techniques in Electronic Discovery for Legal Matters." In Next Generation Search Engines: Advanced Models for Information Retrieval, edited by Christophe Jouis, et al., 174-190. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0330-1.ch008

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Abstract

Electronic discovery (eDiscovery) is the process of collecting and analyzing electronic documents to determine their relevance to a legal matter. Office technology has advanced and eased the requirements necessary to create a document. As such, the volume of data has outgrown the manual processes previously used to make relevance judgments. Methods of text mining and information retrieval have been put to use in eDiscovery to help tame the volume of data; however, the results have been uneven. This chapter looks at the historical bias of the collection process. The authors examine how tools like classifiers, latent semantic analysis, and non-negative matrix factorization deal with nuances of the collection process.

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