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IST Professor, CSE Grad Develop Tools to Access ‘Scholarly Big Data’

Penn State News (01/24/14) Stephanie Koons 

Pennsylvania State University (PSU) researchers have developed recommendation systems for expert and collaborator discovery that enable users to access scholarly big data. “For data-driven research, we have a very good opportunity for big data research because we are one of the few groups that have such a large volume of data,” says PSU’s Hung-Hsuan Chen. The researchers propose CSSeer, a free and publicly available key phrase-based recommendation system for expert discovery based on the CiteSeerX digital library and Wikipedia as an auxiliary resource. The system generates key phrases from the title and the abstract of each document in CiteSeerX, and those key phrases are used to infer the author’s expertise. “The system automatically figures out who are the experts of a given area,” Chen says. CiteSeerX aims to improve the dissemination of scientific literature and to provide improvements in functionality, usability, availability, cost, comprehensiveness, efficiency, and timeliness in the access of scientific and scholarly knowledge. PSU professor C. Lee Giles says the long-term plans for CiteSeer include making the system easier and more efficient to run, improving data-extraction methods, increasing the number of documents, and automating the extraction of tables and figures in documents.

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