Lee Giles

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C. (Clyde) Lee Giles is the David Reese Professor at the College of Information Sciences and Technology at the Pennsylvania State University. He is also Professor of Computer Science and Engineering, Professor of Supply Chain and Information Systems, and Director of the Intelligent Systems Research Laboratory. His graduate degrees are from the University of Michigan and the University of Arizona and his undergraduate degrees are from Rhodes College and the University of Tennessee. His PhD is in optical sciences; his advisor was Harrison H. Barrett. His academic genealogy includes two Nobel laureates and prominent mathematicians.[1]

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[edit] Research

He has been associated with Princeton University, the University of Pennsylvania, Columbia University, the University of Pisa, the University of Trento and the University of Maryland, College Park. Previous positions were at NEC Research Institute (now NEC Labs), Princeton, NJ; Air Force Research Laboratory; and the United States Naval Research Laboratory. He is best known for his work on the creation of novel scientific and academic search engines and digital libraries.

His research interests are in intelligent web and cyberinfrastructure tools, search engines and information retrieval, digital libraries, web services, knowledge and information management and extraction, machine learning, and information and data mining. In these areas he has over 300 publications with some in Nature, Science and the Proceedings of the National Academy of Sciences. His research is well cited with an h-index of 49 according to Google Scholar and over 10,000 total citations as evidenced in CiteSeerX, ISI and the Google Scholar.

He is a Fellow of the Association for Computing Machinery (ACM),[2] IEEE[3] and INNS.

[edit] CiteSeer and Search Engines

His early work published in Science and Nature with Steve Lawrence estimated the size of the web and showed that search engines did not index that much of it. This work also showed that the web had significantly matured and had a diversity of material and resources.

With Steve Lawrence and Kurt Bollacker, Giles was responsible for the creation in 1997 of automatic citation indexing and CiteSeer, a public academic search engine and digital library for Computer and Information Science. Under his direction CiteSeer was moved to and is being maintained at the Pennsylvania State University. CiteSeer has been replaced by the Next Generation CiteSeer, CiteSeerX.

He is the director of the Next Generation CiteSeer project, CiteSeerX, also at the Pennsylvania State University. In addition, he was responsible for the creation of an academic business search engine and digital library, BizSeer (previously known as SmealSearch). With Isaac Councill, he created automatic acknowledgement indexing, permitting for the first time the automatic search and indexing of acknowledged entities in scholarly and research documents.

His recent research in collaboration with Professors Prasenjit Mitra, Karl Mueller, Barbara Garrison and James Kubicki has resulted in the development of a search engine and data portal for chemistry, ChemxSeer, ChemXSeer. With Yang Sun, a novel search engine, BotSeer, was designed that searches and indexes robots.txt files on web sites. The Next Generation CiteSeer, CiteSeerx, came on line in February, 2008, with over one million articles indexed and now with active crawling is approaching 2 million. These new services are based on SeerSuite, a package of open sources tools for searching and indexing academic documents and data.

[edit] References

  1. ^ "Biography Page". 2010. http://clgiles.ist.psu.edu/bio.shtml. Retrieved 2010-10-28. 
  2. ^ "C Lee Giles". ACM Fellows. ACM. 2006. http://fellows.acm.org/fellow_citation.cfm?id=5219597&srt=alpha&alpha=G. Retrieved 2010-01-23. "For contributions to information processing and web analysis." 
  3. ^ "Fellows - G". IEEE Fellows. IEEE. http://www.ieee.org/web/membership/fellows/Alphabetical/gfellows.html#Gh. Retrieved 2010-01-23. "C. Lee Giles 1997: for contributions to the theory and practice of neural networks" 

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