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986,105
TopicSensitive PageRank
, 2002
"... In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search resu ..."
Abstract

Cited by 535 (10 self)
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In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search
Learning to rank using gradient descent
 In ICML
, 2005
"... We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these ideas using a neural network to model the underlying ranking function. We present test results on toy data and on data f ..."
Abstract

Cited by 510 (17 self)
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We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these ideas using a neural network to model the underlying ranking function. We present test results on toy data and on data
Rank Aggregation Methods for the Web
, 2010
"... We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building metasearch engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. Wed ..."
Abstract

Cited by 473 (6 self)
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We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building metasearch engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations
On the axiomatic foundations of ranking systems
 In Proc. 19th International Joint Conference on Artificial Intelligence
, 2005
"... Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type o ..."
Abstract

Cited by 45 (9 self)
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Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type
Incentive Compatible Ranking Systems
"... Ranking systems are a fundamental ingredient of basic ecommerce and Internet Technologies. In this paper we consider the issue of incentives in ranking systems, where agents act in order to maximize their position in the ranking, rather than to get a correct outcome. We consider two di#erent notions ..."
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Cited by 13 (7 self)
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Ranking systems are a fundamental ingredient of basic ecommerce and Internet Technologies. In this paper we consider the issue of incentives in ranking systems, where agents act in order to maximize their position in the ranking, rather than to get a correct outcome. We consider two di
Guaranteed minimumrank solutions of linear matrix equations via nuclear norm minimization
, 2007
"... The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the literature of a diverse set of fields including system identification and control, Euclidean embedding, and collaborative ..."
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Cited by 568 (23 self)
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The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the literature of a diverse set of fields including system identification and control, Euclidean embedding
On the Axiomatic Foundations of Ranking Systems
"... Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type o ..."
Abstract
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Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type
Ranking systems: The PageRank axioms
 In EC ’05: Proceedings of the 6th ACM conference on Electronic commerce
, 2005
"... This paper initiates research on the foundations of ranking systems, a fundamental ingredient of basic ecommerce and Internet Technologies. In order to understand the essence and the exact rationale of page ranking algorithms we suggest the axiomatic approach taken in the formal theory of social ch ..."
Abstract

Cited by 42 (8 self)
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This paper initiates research on the foundations of ranking systems, a fundamental ingredient of basic ecommerce and Internet Technologies. In order to understand the essence and the exact rationale of page ranking algorithms we suggest the axiomatic approach taken in the formal theory of social
Quantifying incentive compatibility of ranking systems
 In Proc. of AAAI06
, 2006
"... Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type o ..."
Abstract

Cited by 16 (8 self)
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Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type
Mechanized grading, Ranking system
, 2012
"... Around 2000, we started to propose to students exercises with mechanized grading. Since, we have been accumulating lots of data that confirm the evidence: the more the students practice, the better they perform at examinations! Therefore, to foster the use of these exercises, we devise a ranking sys ..."
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Around 2000, we started to propose to students exercises with mechanized grading. Since, we have been accumulating lots of data that confirm the evidence: the more the students practice, the better they perform at examinations! Therefore, to foster the use of these exercises, we devise a ranking
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