Rajeev Motwani

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The nearest neighbor problem is the follolving: Given a set of n points P = (PI, . . . ,p,} in some metric space X, preprocess P so as to efficiently answer queries which require finding bhe point in P closest to a query point q E X. We focus on the particularly interesting case of the d-dimensional Euclidean space where X = Wd under some Zp norm. Despite(More)
optimization problem, 275, 277<lb>adaptive adversary, 373<lb>Adleman's Theorem, 39<lb>Adleman,<lb>L., 41, 410, 426<lb>Aggarwal,<lb>A, 362<lb>Aho, AV., 25, 187, 189, 302<lb>Ahuja, R.K., 303<lb>Ajtai, M., 156, 160, 361<lb>Albers, S., 389<lb>Aldous, DJ., 64, 155, 332<lb>Aleliunas,<lb>R, 96, 155<lb>Alford, W.R, 426<lb>all-pairs shortest paths, 278-288,(More)
In this overview paper we motivate the need for and research issues arising from a new model of data processing. In this model, data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying <i>data streams.</i> In addition to reviewing past work relevant to data stream systems and current projects in(More)
We consider the problem of analyzing market-basket data and present several important contributions. First, we present a new algorithm for finding large itemsets which uses fewer passes over the data than classic algorithms, and yet uses fewer candidate itemsets than methods based on sampling. We investigate the idea of item reordering, which can improve(More)
We show that every language in NP has a probablistic verifier that checks membership proofs for it using logarithmic number of random bits and by examining a <italic>constant</italic> number of bits in the proof. If a string is in the language, then there exists a proof such that the verifier accepts with probability 1 (i.e., for every choice of its random(More)
One of the most well-studied problems in data mining is mining for association rules in market basket data. Association rules, whose significance is measured via support and confidence, are intended to identify rules of the type, &#8220;A customer purchasing item A often also purchases item B.&#8221; Motivated by the goal of generalizing beyond market(More)
STREAM is a general-purpose relational Data Stream Management System (DSMS). STREAM supports a declarative query language and flexible query execution plans. It is designed to cope with high data rates and large numbers of continuous queries through careful resource allocation and use, and by degrading gracefully to approximate answers as necessary. A(More)