Divesh Srivastava is the head of the Database Research Department at AT&T Labs-Research. He received his Ph.D. from the University of Wisconsin, Madison, and his B.Tech from the Indian Institute of Technology, Bombay. He is a Fellow of the ACM, on the board of trustees of the VLDB Endowment, and an associate editor of the ACM Transactions on Database Systems. He has served as the associate Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering, and the program committee co-chair of many conferences, including VLDB 2007. He has presented keynote talks at several conferences, including VLDB 2010. His research interests span a variety of topics in data management.

AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

AG Audience

English

90 Minutes

Kaiserslautern

The Deep Web has enabled the availability of a huge amount of useful information and people have come to rely on it to fulfill their information needs in a variety of domains. We present a recent study on the accuracy of data and the quality of Deep Web sources in two domains where quality is important to people's lives: Stock and Flight. We observe that, even in these domains, the quality of the data is less than ideal, with sources providing conflicting, out-of-date and incomplete data. Sources also copy, reformat and modify data from other sources, making it difficult to discover the truth. We describe techniques proposed in the literature to solve these problems, evaluate their strengths on our data, and identify directions for future work in this area.

Susanne Rock

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Saarbrücken

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