A new tangible user interface for machine learning document review

Artificial Intelligence and Law

Volumn 18, Issue 4, 2010, Pages 459-479

  Privault, Caroline ^a   O'Neill, Jacki ^a   Ciriza, Victor ^a   Renders, Jean Michel ^a  

^a XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

Categorization; Clustering; Document review; EDiscovery; Litigation; Machine learning; Tangible user interface; Touch screen; User interface design

Indexed keywords

CATEGORIZATION; CLUSTERING; DOCUMENT REVIEW; EDISCOVERY; LITIGATION; MACHINE LEARNING; TANGIBLE USER INTERFACES; TOUCH SCREEN; USER-INTERFACE DESIGN;

LAWS AND LEGISLATION; LEARNING SYSTEMS; MACHINE DESIGN;

USER INTERFACES;

EID: 79951771884     PISSN: 09248463     EISSN: 15728382     Source Type: Journal    
DOI: 10.1007/s10506-010-9090-z     Document Type: Article

References (20)

1. Attfield S, De Gabrielle S, Blandford A (2009) The loneliness of the long-distance document reviewer: E-Discovery and cognitive ergonomics. In: DESI III workshop at ICAIL, Barcelona, June 2009
2. Barnett T, Godjevac S, Privault C, Renders JM, Wickstrom R (2009) Machine learning classification for document review. In: DESI III Workshop at ICAIL, Barcelona, June 2009 (http://www.law.pitt. edu/DESI3-Workshop/DESI-III-papers. htm)
3. Baron J, Braman R, Withers K, Allman T, Daley M, Paul G (2007) Best practices commentary on the use of search & information retrieval methods in e-Discovery. The Sedona Conference Journal 8: 189-223
4. Belkin NJ (2008) Some(what) grand challenges for information retrieval. ACM SIGIR Forum Arch 42(1):47-54
5. Blair DC, Maron ME (1985) Evaluation of retrieval effectiveness for a full-text document-retrieval system. Commun ACM 28(3):289-299 (Pubitemid 15599385)
6. Davis JE, Matus WC (2008) Does your search pass judicial scrutiny? NY Law J. http://www.law.com/ jsp/nylj/index.jsp
7. Gaussier E, Goutte C, Popat K, Chen F (2002) A hierarchical model for clustering and categorising documents. In: Proceedings of the 24th BCS-IRSG European Colloquium on IR research: Advances in information retrieval, 25-27 March 2002, pp 229-247
8. Greenwood A (2007) Attorney at Blah. In: Washington city paper. http://www.washingtoncitypaper.com/ display.php?id=34054
9. Hearst MA (2009) Search user interfaces. Cambridge University Press, Cambridge
10. Hofmann T (1999) Probabilistic latent semantic analysis. In: Proceedings of 15th conference on uncertainty in artificial intelligence. Morgan Kaufmann, pp 289-296
11. Kershaw A (2005) Automated document review proves its reliability. Digit Discov e-Evid 5(11). http://www.akershaw.com/iframes/akershaw-publications.html
12. Liddy E (2005) Document retrieval, automatic. In: Encyclopedia of language and linguistics, 2nd edn. Elsevier, Amsterdam
13. Love N (2006) Automating document review. In: CS224n final project http://nlp.stanford.edu/courses/ cs224n/2006/fp/natlove-1-natlove-cs224n-final. pdf
14. McNee MS, Arnette B (2008) Productivity as a metric for visual analytics: Reflections on e-discovery. In: Proceedings of the BELIV'08 conference, Florence, Italy
15. Roitblat HL, Kershaw A, Oot P (2010) Document categorization in legal electronic discovery: Computer classification vs. manual review. JASIST 61(1):70-80
16. Sebastiani F (2002) Machine learning in automated text categorization. ACM Comput Surv 34(1):1-47
17. Smart Document Review (2010) http://www.youtube.com/watch?v=tNd8SGBtmzI
18. Tomlinson S, Oard DW, Baron JR, Thompson P (2007) Overview of the TREC 2007 legal track. In: TREC 2007 (http://trec-legal.umiacs.umd.edu/)
19. Turtle H (1994) Natural language vs. Boolean query evaluation: A comparison of retrieval performance. In: Proceedings of the 17th ACM SIGIR, Dublin, pp 212-220
20. Victor Stanley Inc. v. Creative Pipe Inc. 2008 WL 2221841 (D.Md. 2008). http://ralphlosey.files.word press.com/2008/06/victorstanleymomay29-08final.pdf