Abstract: CiteSeer, a public online computer and information science search engine and digital library, was a radical departure from the traditional methods of academic and scientific document access and analysis. CiteSeer, now hosted at Penn State, has over 700,000 documents and, with a million page views a day, has become one of the most popular academic document search engines in science. The CiteSeer model is also portable and was recently extended to academic business documents (SMEALSearch). CiteSeer is based on these features: actively acquiring new documents, automatic citation indexing, and automatic linking of citations and documents. The new Google Scholar does similar citation indexing and linking. Why has CiteSeer been so popular and how should it progress? We discuss this and the Next Generation CiteSeer project, which will emphasize CiteSeer as a research tool and facilitator, and which will explore new intelligent algorithms for providing improved and new indexes, enhanced document access, expanded and automatic document gathering, collaboratories, new data resources, active mirroring, and web services. As example, we discuss our new work on automatic acknowledgement indexing, which provides insight into the impact of acknowledged individuals and funding agencies.

Speaker's Bio: In 2000 Dr. C. Lee Giles left NEC Research Institute, now NEC Labs, to become the David Reese Professor at the School of Information Sciences and Technology.  He is also Professor of Computer Science and Engineering, Professor of Supply Chain and Information Systems, and Associate Director of Research at the eBusiness Research Center at the Pennsylvania State University, University Park, PA. He has been associated with Princeton University, the University of Pennsylvania, Columbia University, the University of Pisa and the University of Maryland; and has taught at all of the above.

His current research and consulting interests are in intelligent information processing systems:

• Intelligent portals, novel web tools, search engines, web search and measurement.
• Business models for search and search engines.
• Knowledge management and extraction, information and data mining, digital libraries and web databases.
• Computational issues in e-commerce, the e-world, markets and betting.
• Novel applications of neural and machine learning, agents and AI in: web computing, knowledge management, databases, information retrieval, telecommunications, parallel and distributed computing, multi-media, computer systems, neuroscience, adaptive control, system identification, networking, pattern recognition and signal processing, language processing, time series and finance.

His research is or has been supported by NSF, NASA, DARPA, Microsoft, FAST Search and Transfer, Ford, IBM, Lockheed-Martin, Lucent, Department of Treasury, and NEC. He has twice received an IBM Distinguished Faculty Award. He has consulted for or been on advisory boards of NEC, FAST Search and Transfer, PJM, KXEN, US Department of Treasury, and the US Department of Defense.

He has published over 200 journal and conference papers, book chapters, edited books and proceedings in these areas. His recent coauthored paper in the Proceedings of the National Academy of Sciences created an automatic acknowledgement indexing methodology and showed that various funding agencies and individuals in computer and information science are much more acknowledged than others. In 2002, he coauthored the paper "Winners Don't Take All" published also  in the Proceedings of the National Academy of Sciences on how the topic based web does not follow a power law distribution. In 1998, he coauthored a paper published in Science on the size and search engine coverage of the Web that was well cited in the popular press and in 1999 a well received follow-up paper in Nature. Several of his papers have won or been nominated for best paper awards and have been reprinted in edited collections. His research has been highlighted in many places including the Society for Industrial and Applied Mathematics (SIAM) news, Wired Magazine, the Wall Street Journal, the Washington Post, and Business 2.0.

He has been involved in the creation and development of various novel search engines and digital libraries. He was one of the creators of the popular computer science search engine, CiteSeer, an autonomous citation indexing search engine and digital library for computer science documents. CiteSeer is now hosted at the School of Information Sciences and Technology at Penn State University.  More recently, he created the niche search engine eBizSearch, a search engine for e-business documents, and, SMEALSearch, a search engine and digital library for academic business documents.

Dr. Giles plays an active professional role in the technical and scientific communities. He serves on many related conference program committees and has helped organize many related meetings and workshops. He has given many invited talks and seminars. He has been or is an advisor and reviewer to USA and other government and university research programs. He has served or is currently serving on the editorial boards of IEEE Intelligent Systems, IEEE Transactions on Knowledge and Data Engineering, Machine Learning Journal, Computational Intelligence and Applications,  IEEE Transactions on Neural Networks, Journal of Computational Intelligence in Finance, Journal of Parallel and Distributed Computing, Neural Networks, Neural Computation, and Academic Press.

He is a Fellow of the IEEE and of the International Neural Network Society, and a member of AAAI and ACM. He is also a member of Sigma Xi, Tau Beta Pi, and Eta Kappa Nu. His previous positions include a Senior Research Scientist at NEC Research Institute (now NEC Labs), Princeton, NJ; a Program Manager at the Air Force Office of Scientific Research in Washington, D.C.; a research scientist at the Naval Research Laboratory, Washington, D.C.; and an Assistant Professor of Electrical and Computer Engineering at Clarkson University, Potsdam, N.Y. During part of his graduate education he was a research engineer at Ford Motor Company's Scientific Research Laboratory. His graduate degrees are from the University of Michigan and the University of Arizona. His academic genealogy includes two Nobel laureates and prominent mathematicians.