Results 1 - 10 of 141

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
results, we propose computing a set of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic. By using these (precomputed) biased PageRank vectors to generate query-specific importance scores for pages at query

What is Twitter, a Social Network or a News Media?

by Haewoon Kwak, Changhyun Lee, Hosung Park, Sue Moon
"... Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological charac ..."
Abstract - Cited by 991 (12 self) - Add to MetaCart
Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological

Topic-sensitive pagerank: A context-sensitive ranking algorithm for web search

by Taher H. Haveliwala - IEEE Transactions on Knowledge and Data Engineering , 2003
"... Abstract—The original PageRank algorithm for improving the ranking of search-query results computes a single vector, 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 results, we propose ..."
Abstract - Cited by 237 (2 self) - Add to MetaCart
computing a set of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic. For ordinary keyword search queries, we compute the topicsensitive PageRank scores for pages satisfying the query using the topic

Twitterrank: finding topic-sensitive influential twitterers

by Jianshu Weng, Ee-peng Lim, Jing Jiang, Qi He - IN IN PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING , 2010
"... This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called “following”, in which each user can choose who she wants to “follow” to receive tweets from without requir ..."
Abstract - Cited by 285 (12 self) - Add to MetaCart
of “reciprocity” can be explained by phenomenon of homophily [14]. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking

Traps and pitfalls of topic-biased PageRank

by Paolo Boldi, Roberto Posenato, Massimo Santini, Sebastiano Vigna - In WAW 2006. Fourth Workshop on Algorithms and Models for the Web-Graph, Lecture Notes in Computer Science , 2007
"... We discuss a number of issues in the definition, computation and comparison of PageRank values that have been addressed sparsely in the literature, often with contradictory approaches. We study the difference between weakly and strongly preferential PageRank, which patch the dangling nodes with diff ..."
Abstract - Cited by 12 (3 self) - Add to MetaCart
We discuss a number of issues in the definition, computation and comparison of PageRank values that have been addressed sparsely in the literature, often with contradictory approaches. We study the difference between weakly and strongly preferential PageRank, which patch the dangling nodes

Utility analysis for topically biased PageRank

by Christian Kohlschütter - In WWW ’07: Proceedings of the 16th International Conference on World Wide Web , 2007
"... PageRank is known to be an efficient metric for computing general document importance in the Web. While commonly used as a one-size-fits-all measure, the ability to produce topically biased ranks has not yet been fully explored in detail. In particular, it was still unclear to what granularity of “t ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
PageRank is known to be an efficient metric for computing general document importance in the Web. While commonly used as a one-size-fits-all measure, the ability to produce topically biased ranks has not yet been fully explored in detail. In particular, it was still unclear to what granularity

Topic-based PageRank on Author Co- citation Networks

by Ying Ding
"... Abstract Ranking authors is vital for identifying a researcher's impact and his standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes to ..."
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Abstract Ranking authors is vital for identifying a researcher's impact and his standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes

Incremental PageRank Computation on evolving graphs

by Prasanna Desikan, Nishith Pathak - in WWW , 2005
"... Link Analysis has been a popular and widely used Web mining technique, especially in the area of Web search. Various ranking schemes based on link analysis have been proposed, of which the PageRank metric has gained the most popularity with the success of Google. Over the last few years, there has b ..."
Abstract - Cited by 19 (2 self) - Add to MetaCart
been significant work in improving the relevance model of PageRank to address issues such as personalization and topic relevance. In addition, a variety of ideas have been proposed to address the computational aspects of PageRank, both in terms of efficient I/O computations and matrix computations

Letor: Benchmark dataset for research on learning to rank for information retrieval

by Tie-yan Liu, Jun Xu, Tao Qin, Wenying Xiong, Hang Li - In Proceedings of SIGIR 2007 Workshop on Learning to Rank for Information Retrieval , 2007
"... This paper is concerned with learning to rank for information retrieval (IR). Ranking is the central problem for information retrieval, and employing machine learning techniques to learn the ranking function is viewed as a promising approach to IR. Unfortunately, there was no benchmark dataset that ..."
Abstract - Cited by 156 (16 self) - Add to MetaCart
the datasets, including both conventional features, such as term frequency, inverse document frequency, BM25, and language models for IR, and features proposed recently at SIGIR, such as HostRank, feature propagation, and topical PageRank. We have then packaged LETOR with the extracted features, queries

Personalizing PageRank Based on Domain Profiles

by Mehmet S. Aktas, Mehmet A. Nacar, Filippo Menczer - In Proc. of WebKDD 2004: KDD Workshop on Web Mining and Web Usage Analysis , 2004
"... Personalized versions of PageRank have been proposed to rank the results of a search engine based on a user's topic or query of interest. This paper introduces a methodology for personalizing PageRank vectors based on URL features such as Internet domains. Users specify interest profiles as bin ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
Personalized versions of PageRank have been proposed to rank the results of a search engine based on a user's topic or query of interest. This paper introduces a methodology for personalizing PageRank vectors based on URL features such as Internet domains. Users specify interest profiles
Results 1 - 10 of 141