On the feasibility of low-rank approximation for personalized PageRank

András A. Benczúr, Károly Csalogány, Tamás Sarlós
2005 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 an
more » ... roximate personalized PageRank by multiplying an n × k, a k × n matrix and the n-dimensional personalization vector. Since low-rank approximations are accurate on dense regions, we hope that our technique will combine well with known algorithms.
doi:10.1145/1062745.1062824 dblp:conf/www/BenczurCS05 fatcat:lzhl7ee5vjg6ver5v7ln5h4jte