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Topic-Sensitive PageRank

by Taher Haveliwala , 2002
"... In the original PageRank algorithm for improving the ranking of search-query 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 543 (10 self) - Add to MetaCart
In the original PageRank algorithm for improving the ranking of search-query 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

by Chris Burges, Tal Shaked, Erin Renshaw, Matt Deeds, Nicole Hamilton, Greg Hullender - 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 534 (17 self) - Add to MetaCart
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

Cumulated Gain-based Evaluation of IR Techniques

by Kalervo Järvelin, Jaana Kekäläinen - ACM Transactions on Information Systems , 2002
"... Modem large retrieval environments tend to overwhelm their users by their large output. Since all documents are not of equal relevance to their users, highly relevant documents should be identified and ranked first for presentation to the users. In order to develop IR techniques to this direction, i ..."
Abstract - Cited by 694 (3 self) - Add to MetaCart
along the ranked result list. The second one is similar but applies a discount factor on the relevance scores in order to devaluate late-retrieved documents. The third one computes the relative-tothe -ideal performance of IR techniques, based on the cumulative gain they are able to yield. The novel

Rank Aggregation Methods for the Web

by Cynthia Dwork, Ravi Kumar, Moni Naor, D. Sivakumar , 2010
"... We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. Wed ..."
Abstract - Cited by 478 (6 self) - Add to MetaCart
We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations

Amortized Efficiency of List Update and Paging Rules

by Daniel D. Sleator, Robert E. Tarjan , 1985
"... In this article we study the amortized efficiency of the “move-to-front” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes 0(i) time, we show that move-to-front is within a constant factor of optimum amo ..."
Abstract - Cited by 824 (8 self) - Add to MetaCart
among a wide class of list maintenance rules. Other natural heuristics, such as the transpose and frequency count rules, da not share this property. We generalize our results to show that move-to-front is within a constant factor of optimum as long as the access cost is a convex function. We also study

Video google: A text retrieval approach to object matching in videos

by Josef Sivic, Andrew Zisserman - In ICCV , 2003
"... We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, ill ..."
Abstract - Cited by 1636 (42 self) - Add to MetaCart
-computed (using vector quantization), and inverted file systems and document rankings are used. The result is that retrieval is immediate, returning a ranked list of key frames/shots in the manner of Google. The method is illustrated for matching on two full length feature films. 1.

Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval Results

by Marti A. Hearst, Jan O. Pedersen , 1996
"... We present Scatter/Gather, a cluster-based document browsing method, as an alternative to ranked titles for the organization and viewing of retrieval results. We systematically evaluate Scatter/Gather in this context and find significant improvements over similarity search ranking alone. This resul ..."
Abstract - Cited by 480 (5 self) - Add to MetaCart
We present Scatter/Gather, a cluster-based document browsing method, as an alternative to ranked titles for the organization and viewing of retrieval results. We systematically evaluate Scatter/Gather in this context and find significant improvements over similarity search ranking alone

The use of MMR, diversity-based reranking for reordering documents and producing summaries

by Jaime Carbonell, Jade Goldstein - In SIGIR , 1998
"... jadeQcs.cmu.edu Abstract This paper presents a method for combining query-relevance with information-novelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR) criterion strives to reduce redundancy while maintaining query relevance in re-ranking retrieved docum ..."
Abstract - Cited by 768 (14 self) - Add to MetaCart
systems. However, the clearest advantage is demonstrated in constructing non-redundant multi-document summaries, where MMR results are clearly superior to non-MMR passage selection. 2 Maximal Marginal Relevance Most modem IR search engines produce a ranked list of retrieved documents ordered by declining

An Efficient Boosting Algorithm for Combining Preferences

by Raj Dharmarajan Iyer , Jr. , 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
Abstract - Cited by 727 (18 self) - Add to MetaCart
search strategies, each of which is a query expansion for a given domain. For this task, we compare the performance of RankBoost to the individual search strategies. The second experiment is a collaborative-filtering task for making movie recommendations. Here, we present results comparing Rank

Searching Distributed Collections With Inference Networks

by James P. Callan, Zhihong Lu, W. Bruce Croft - IN PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL , 1995
"... The use of information retrieval systems in networked environments raises a new set of issues that have received little attention. These issues include ranking document collections for relevance to a query, selecting the best set of collections from a ranked list, and merging the document rankings t ..."
Abstract - Cited by 471 (36 self) - Add to MetaCart
The use of information retrieval systems in networked environments raises a new set of issues that have received little attention. These issues include ranking document collections for relevance to a query, selecting the best set of collections from a ranked list, and merging the document rankings
Results 1 - 10 of 51,721