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EVALUATION OF THE PAGERANK ALGORITHM EFFECTIVENESS

by Kazimierz Worwa, Gustaw Konopacki
"... In this paper the challenges in building good search engines are discussed. Many of the search engines use well-known information retrieval algorithms and tech-niques. They use Web crawlers to maintain their index databases amortizing the cost of crawling and indexing over the millions of queries re ..."
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received by them. Web crawl-ers are programs that exploit the graph structure of the Web to move from page to page. Paper analyses the PageRank algorithm one of these Web crawlers. The results of the impact of the PageRank parameter value on the effectiveness of determining the so-called PageRank vector

ON GRAPH ISOMORPHISM AND THE PAGERANK ALGORITHM

by Christopher J. Augeri , 2008
"... ..."
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A MULTIDIMENSIONAL PAGERANK ALGORITHM OF LITERATURES

by Kun Yu, Xiaobing Chen, Jianhong Chen
"... Literature is usually evaluated based on impact factor, cited information or the quality of literature database. Here, some more exact evaluation schemes and algorithms are investigated and a synthetically reputation model and its evaluation algorithm are proposed. The reputation model integrates mu ..."
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model, the relationships belong to different classes and have different importance that is great different from PageRank which regard all links as the same class. We propose a centralized algorithm that can compute the reputation most exactly and a distributed version that can run in P2P systems

CONVERGENCE ANALYSIS OF AN IMPROVED PAGERANK ALGORITHM

by Ilse C. F, Ipsen, Steve Kirkland
"... Abstract. The iterative aggregation/disaggregation (IAD) method is an improvement of the PageRank algorithm used by the search engine Google to compute stationary probabilities of very large Markov chains. In this paper the convergence, in exact arithmetic, of the IAD method is analyzed. The IAD met ..."
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Abstract. The iterative aggregation/disaggregation (IAD) method is an improvement of the PageRank algorithm used by the search engine Google to compute stationary probabilities of very large Markov chains. In this paper the convergence, in exact arithmetic, of the IAD method is analyzed. The IAD

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 ..."
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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

SURVEY ON PAGERANK ALGORITHMS USING WEB-LINK STRUCTURE

by Sowmya M , V S Sreelaxmi , Anil G N
"... ABSTRACT Pagerank vector for ranking the search-query results, which made use of link structure of the Web, to get the importance of Web pages, particularly independent of any search query. To get correct search results, we propose calculating a set of PageRank vectors, biased with a set of archety ..."
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vector. We compute the topic-sensitive PageRank scores for pages for normal keyword search queries, sufficing the query using the topic of the keywords. PageRank scores using context in which the query appeared. For better ordering of web pages compute an associated PageRank algorithm for search engines

S.: Promise and pitfalls of extending google’s pagerank algorithm to citation networks

by Sergei Maslov, Sidney Redner - J. Neurosci , 2008
"... Editor’s Note: The misuse of journal impact factor in hiring and promotion decisions is a growing concern. This article is one in a series of invited commentaries in which authors discuss this problem and consider alternative measures of an individual’s impact. ..."
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Editor’s Note: The misuse of journal impact factor in hiring and promotion decisions is a growing concern. This article is one in a series of invited commentaries in which authors discuss this problem and consider alternative measures of an individual’s impact.

Application of the pagerank algorithm for ranking locations of a production network

by Bernd Scholz-reiter, Fabian Wirth, Sergey Dashkovskiy, Thomas Makuschewitz, Michael Kosmykov, Michael Schönlein - In Proceedings of the 42nd CIRP Conference on Manufacturing Systems
"... In order to investigate the dynamics of large-scale production networks it is essential to derive representative models of lower size. Against this background two questions occur: How to identify locations that might be neglected? How to identify locations that are highly important for the original ..."
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network? In this paper it will be presented an approach that allows determining the relative importance of locations within one production network. The approach is based on an adaptation of the PageRank algorithm used by Google. The algorithm considers both the network structure and the intensity

IMPROVING ACCUMULATED RECOMMENDATION SYSTEM A COMPARATIVE STUDY OF DIVERSITY USING PAGERANK ALGORITHM TECHNIQUE

by Dasari Siva Krishna, K. Rajani Devi
"... Recommender systems can use data mining techniques for making recommendations using knowledge learnt from the action and attributes of users. In a world where the number of choices can be overwhelming, recommender systems help users find and evaluate items of interest. Previous works introduce and e ..."
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and explore a number of item ranking techniques that can generate recommendations that have substantially higher aggregate diversity across all users while maintaining comparable levels of recommendation accuracy. In this paper we implement PageRank algorithm and recommendation tool with rating techniques

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
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
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