SimRank and its variants in academic literature data: Measures and evaluation

Citations

SCOPUS

4

초록

SimRank is a well-known link-based similarity measure that can be applied on a citation graph to compute similarity of academic literature data. The intuition behind SimRank is that two objects are similar if they are referenced by similar objects. SimRank has attracted a growing interest in the areas of data mining and information retrieval recently. Despite of the current success of SimRank, it has some problems that negatively affect its effectiveness in similarity computation. In this paper, we discuss the three existing problems of SimRank, present SimRank variants that have been proposed to solve those problems, and evaluate the effectiveness of SimRank and its variants in similarity computation for academic literature data by conducting extensive experiments on a real-world dataset.

키워드

Academic literature dataSimilaritySimRankSimRank problemsSimRank variantsData miningAcademic literatureCitation graphsExisting problemsReal-worldSimilaritySimilarity computationSimilarity measureSimrankProblem solving
제목
SimRank and its variants in academic literature data: Measures and evaluation
저자
Hamedani, Masoud ReyhaniKim, Sang-Wook
DOI
10.1145/2851613.2851811
발행일
2016-04
유형
Conference Paper
저널명
Proceedings of the ACM Symposium on Applied Computing
페이지
1102 ~ 1107