Computer Science – Databases
Scientific paper
2012-01-31
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 5, pp. 442-453 (2012)
Computer Science
Databases
VLDB2012
Scientific paper
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity score between two nodes in a graph, and it has been successfully used in many applications such as automatic image captioning, recommender systems, and link prediction. The goal of this work is to find nodes that have top-k highest proximities for a given node. Previous approaches to this problem find nodes efficiently at the expense of exactness. The main motivation of this paper is to answer, in the affirmative, the question, `Is it possible to improve the search time without sacrificing the exactness?'. Our solution, {it K-dash}, is based on two ideas: (1) It computes the proximity of a selected node efficiently by sparse matrices, and (2) It skips unnecessary proximity computations when searching for the top-k nodes. Theoretical analyses show that K-dash guarantees result exactness. We perform comprehensive experiments to verify the efficiency of K-dash. The results show that K-dash can find top-k nodes significantly faster than the previous approaches while it guarantees exactness.
Fujiwara Yasuhiro
Kitsuregawa Masaru
Nakatsuji Makoto
Onizuka Makoto
No associations
LandOfFree
Fast and Exact Top-k Search for Random Walk with Restart does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Fast and Exact Top-k Search for Random Walk with Restart, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fast and Exact Top-k Search for Random Walk with Restart will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-57193