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Semantics-based legal citation network
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International Conference on Artificial Intelligence and Law archive
Proceedings of the 11th international conference on Artificial intelligence and law table of contents
Stanford, California
SESSION: Legal information retrieval table of contents
Pages: 123 - 130  
Year of Publication: 2007
ISBN:978-1-59593-680-6
Authors
Paul Zhang  New Technology Research, LexisNexis, Miamisburg, OH
Lavanya Koppaka  New Technology Research, LexisNexis, Miamisburg, OH
Sponsor
: International Association for Artificial Intelligence and Law
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 27,   Downloads (12 Months): 100,   Citation Count: 2
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ABSTRACT

We describe and discuss the use of semantics-based citation networks in a new legal research tool. Such networks are generated based on citation relations between cases found in legal corpora as well as legal issues being discussed with these citations. Unlike traditional tools, the System allows legal professionals to efficiently study legal issues without having to go through whole cases or tedious manual citation search. This shift of focus from cases to individual issues within cases would greatly reduce time required for attorneys and legal scholars who have specific research problems in mind.

The Systems User Interface (UI) allows users to easily navigate in the citation networks and study how citations are interrelated and how legal issues have evolved in the past. Various forms of natural language processing (NLP) technologies are used in building the metadata behind the prototype. Formal evaluation confirmed the Systems capability of accurately identifying citations relevant to given legal issues.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Paul Zhang: colleagues
Lavanya Koppaka: colleagues