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Information retrieval for e-discovery

Published: 19 July 2010 Publication History

Abstract

Discovery, the process under which parties to legal cases must reveal documents relevant to the disputed issues is a core aspect of trials in the United States, and a lesser but important factor in other countries. Discovery on documents stored in computerized systems (known variously as electronic discovery, e-discovery, e-disco, EDD, and ED) is increasingly the major factor in discovery, and has become a multi-billion dollar industry.
I will discuss the basics of e-discovery, the scale and diversity of the materials involved, and the economics of identifying and reviewing potentially responsive material. I will then focus on three major IR areas of interest: search, supervised machine learning (including text classification and relevance feedback), and interface support for manual relevance assessment. For each, I will discuss technologies currently used in e-discovery, the evaluation methods applicable to measuring effectiveness, and existing research results not yet seeing commercial practice.
I will also outline research directions that, if successfully pursued, would potentially be of great interest in e-discovery applications. A particular focus will be on areas where researchers can make progress without access to operational e-discovery environments or "realistic" test collections. Connections will be drawn with the use of IR in related tasks, such as enterprise search, criminal investigations, intelligence analysis, historical research, truth and reconciliation commissions, and freedom of information (open records or sunshine law) requests.

Cited By

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  • (2024)High Recall Retrieval Via Technology-Assisted ReviewProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3661376(2987-2988)Online publication date: 10-Jul-2024
  • (2014)Relevance-Ranked Domain-Specific Synonym DiscoveryAdvances in Information Retrieval10.1007/978-3-319-06028-6_11(124-135)Online publication date: 2014

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cover image ACM Conferences
SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
July 2010
944 pages
ISBN:9781450301534
DOI:10.1145/1835449
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2010

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Author Tags

  1. OCR
  2. backups
  3. computer forensics
  4. document formats
  5. duplicate detection
  6. e-mail
  7. electronic mail
  8. text mining

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SIGIR '10
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SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;
Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all
  • (2024)High Recall Retrieval Via Technology-Assisted ReviewProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3661376(2987-2988)Online publication date: 10-Jul-2024
  • (2014)Relevance-Ranked Domain-Specific Synonym DiscoveryAdvances in Information Retrieval10.1007/978-3-319-06028-6_11(124-135)Online publication date: 2014

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