Deepak Ravichandran
Deepak Ravichandran is currently a Research Scientist at Google. His general research interests are in the area of Natural Language Processing and Unsupervised Machine Learning algorithms. He received his Ph.D. in computer science from the University of Southern California in 2005.
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A Tale of Two (Similar) Cities: Inferring City Similarity Through Geo-Spatial Query Log Analysis
Rohan Seth
Michele Covell
D. Sivakumar
Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (2011)
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Understanding the backgrounds and interest of the people who are consuming a piece of content, such as a news story, video, or music, is vital for the content producer as well the advertisers who rely on the content to provide a channel on which to advertise. We extend traditional search-engine query log analysis, which has primarily concentrated on analyzing either single or small groups of queries or users, to examining the complete query stream of very large groups of users – the inhabitants of 13,377 cities across the United States. Query logs can be a good representation of the interests of the city’s inhabitants and a useful characterization of the city itself. Further, we demonstrate how query logs can be effectively used to gather city-level statistics sufficient for providing insights into the similarities and differences between cities. Cities that are found to be similar through the use of query analysis correspond well to the similar cities as determined through other large-scale and time-consuming direct measurement studies, such as those undertaken by the Census Bureau.
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Text Classification Through Time: Efficient Label Propagation in Time-Based Graphs
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D. Sivakumar
International Conference on Knowledge Discovery and Information Retrieval (2009)
Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks
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Joseph Reisinger
Marius Pasca
Rahul Bhagat
Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2008), Association for Computational Linguistics, Honolulu, Hawaii, pp. 582-590
Video Suggestion and Discovery for YouTube: Taking Random Walks Through the View Graph
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Rohan Seth
D. Sivakumar
Yushi Jing
Mohamed Aly
WWW-2008
