Manish S. Gupta

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In entity-relation (ER) graphs (V,E), nodes V represent typed entities and edges E represent typed relations. For dynamic personalized PageRank queries, nodes are ranked by their steady-state probabilities obtained using the standard random surfer model. In this work, we propose a framework to answer top-k graph conductance queries. Our top-k ranking(More)
Personalized PageRank, related to random walks with restarts and conductance in resistive networks, is a frequent search paradigm for graph-structured databases. While efficient batch algorithms exist for static whole-graph PageRank, interactive query-time personalized PageRank has proved more challenging. Here we describe how to select and build indices(More)
Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "pay for performance" business models. We learn regression models using features of the job, optional click history of job, features of "related" jobs. We show that our models predict CTR much(More)
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