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Because of the ease of electronic dissemination, the world of scientific literature on the Web has grown rapidly, becoming a large, highly current database of published research. This acceleration of publication has exacerbated the difficulty researchers face keeping up-to-date on relevant new research trends. Automatic tools to help researchers keep up with the latest relevant publications will be increasingly important. One such tool, CiteSeer, is an automatic generator of scientific literature databases. It uses sophisticated acquisition, parsing, and presentation methods to eliminate most of the manual effort required to perform a literature survey of publications on the Web. It also includes a personalized recommendation system that uses browsing behavior and automatic learning to adapt to individual research interests, even as they change over time. CiteSeer can proactively recommend new relevant research papers as they appear on the Web as well as discover new citations, keywords, and authors that might be indicative of novel research trends of interest to the user.
citation index, digital library, information filtering, user profile

K. D. Bollacker, C. L. Giles and S. Lawrence, "Discovering Relevant Scientific Literature on the Web," in IEEE Intelligent Systems, vol. 15, no. , pp. 42-47, 2000.
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