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On the feasibility of low-rank approximation for personalized PageRank
Special interest tracks and posters of the 14th international conference on World Wide Web - WWW '05
Personalized PageRank expresses backlink-based page quality around user-selected pages in a similar way to PageRank over the entire Web. Algorithms for computing personalized PageRank on the fly are either limited to a restricted choice of page selection or believed to behave well only on sparser regions of the Web. In this paper we show the feasibility of computing personalized PageRank by a k < 1000 lowrank approximation of the PageRank transition matrix; by our algorithm we may compute andoi:10.1145/1062745.1062824 dblp:conf/www/BenczurCS05 fatcat:lzhl7ee5vjg6ver5v7ln5h4jte