Fast Ad-Hoc Search Algorithm for Personalized PageRank

Yasuhiro FUJIWARA  Makoto NAKATSUJI  Hiroaki SHIOKAWA  Takeshi MISHIMA  Makoto ONIZUKA  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D    No.4    pp.610-620
Publication Date: 2017/04/01
Publicized: 2017/01/23
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016AWI0002
Type of Manuscript: Special Section INVITED PAPER (Special Section on Award-winning Papers)
Personalized PageRank,  ad-hoc,  fast,  algorithm,  

Full Text: FreePDF(499.7KB)

Personalized PageRank (PPR) is a typical similarity metric between nodes in a graph, and node searches based on PPR are widely used. In many applications, graphs change dynamically, and in such cases, it is desirable to perform ad hoc searches based on PPR. An ad hoc search involves performing searches by varying the search parameters or graphs. However, as the size of a graph increases, the computation cost of performing an ad hoc search can become excessive. In this paper, we propose a method called Castanet that offers fast ad hoc searches of PPR. The proposed method features (1) iterative estimation of the upper and lower bounds of PPR scores, and (2) dynamic pruning of nodes that are not needed to obtain a search result. Experiments confirm that the proposed method does offer faster ad hoc PPR searches than existing methods.

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