Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
SimFusion: measuring similarity using unified relationship matrix
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
P-Rank: a comprehensive structural similarity measure over information networks
Proceedings of the 18th ACM conference on Information and knowledge management
ASAP: towards accurate, stable and accelerative penetrating-rank estimation on large graphs
WAIM'11 Proceedings of the 12th international conference on Web-age information management
SimFusion+: extending simfusion towards efficient estimation on large and dynamic networks
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
On the efficiency of estimating penetrating rank on large graphs
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
ASCOS: an asymmetric network structure COntext similarity measure
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Algorithms defining similarities between objects of an information network are important of many IR tasks. SimRank algorithm and its variations are popularly used in many applications. Many fast algorithms are also developed. In this note, we first reformulate them as random walks on the network and express them using forward and backward transition probably in a matrix form. Second, we show that P-Rank (SimRank is only the special case of P-Rank) has a unique solution of eeT when decay factor c is equal to 1. We also show that SimFusion algorithm is a special case of P-Rank algorithm and prove that the similarity matrix of SimFusion is the product of PageRank vector. Our experiments on the web datasets show that for P-Rank the decay factor c doesn't seriously affect the similarity accuracy and accuracy of P-Rank is also higher than SimFusion and SimRank.