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Talks & Seminars
Title: Workshop on Web Mining
Dr. Manish Gupta, Microsoft (India) R&D Private Ltd.
Date & Time: February 7, 2015 10:30
Venue: F. C. Kohli Auditorium, 01st Floor, B Block, Department of Computer Science and Engineering, Kanwal Rekhi (KReSIT) Building
Abstract:
This workshop will be held in two sessions - Session 1 from 10:30 am to 12:30 pm and Session 2 from 02:00 pm to 04:00 pm. This 4 hour workshop aims to provide a conceptual and practical understanding of various aspects of web mining, starting with the basics of web search to discussions about recent topics studied in the World Wide Web community. The discussion will take the participants through understanding of the basic information retrieval concepts, web mining concepts and applications. The workshop is divided into 10 modules (each of about 20 minutes) as follows: • Web search basics: Document representation, inverted index, crawling • Relevance Ranking • Link Analysis • Recommendation Systems • Social Networks and Influence Analysis • Analysis of Microblogs • Entity Mining • Mining Structured Information from the Web • Query Log Mining • Crowdsourcing With new forms and large volume of data availability, web mining is a very fast changing field. This course will help attendees to get abreast of the latest developments in the field.
Speaker Profile:
Manish Gupta (http://research.microsoft.com/en-us/people/gmanish/) is a Senior Applied Scientist at the Bing team in Microsoft India R&D Private Limited at Hyderabad, India. He is also an Adjunct Faculty at International Institute of Information Technology, Hyderabad. He received his Masters in Computer Science from IIT Bombay in 2007 and his Ph.D. from the University of Illinois at Urbana-Champaign in 2013. Before this, he worked for Yahoo! Bangalore for two years. His research interests are in the areas of web mining, data mining and information retrieval. He has published more than 30 research papers in referred journals and conferences, including ICDE, KDD, PKDD, SDM, WWW conferences. He has also co-authored a book on Outlier Detection for Temporal Data.
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