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Abstract: In this paper we are describing a program that automatically selects reviewers for submitted Artificial Intelligence papers. This paper is a response to one of the challenge problems presented at IJCAI 1997. The program relies on a central knowledge/database of AI researchers and their areas of specialization. Several filter programs derive this knowledge from publication data and home pages on the World-Wide Web and from a well-known AI Genealogy. The Core Reviewer Selection Program relies on... (Update)
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BibTeX entry: (Update)
@misc{ geller-challenge,
author = "James Geller and Richard Scherl",
title = "Challenge: Technology for Automated Reviewer Selection",
url = "citeseer.ist.psu.edu/512195.html" }
Citations (may not include all citations):187 Transformation-based error-driven learning and natural langu.. - Brill - 1995
106 Some advances in transformation-based part of speech tagging.. - Brill - 1994
79 Automatic Information Orga- nization and Retrieval (context) - Salton - 1968
2 uni-trier (context) - Hoff, pranger - 1997
2 can prove the value of AI by using AI (context) - Geller, How - 1997
1 edu gellerchallenge (context) - http, njit et al. - 1997
1 and Giuseppe Santucci (context) - De Rosa, Catarci et al. - 1998
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1 Talking about AI: Socially defined linguistic subcontexts in.. - Steier, Belew - 1994
Documents on the same site (http://www.cs.njit.edu/~scherl/projects.html):
Challenge: How IJCAI 1999 can Prove the Value of AI by Using AI - Geller (Correct)
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