Online bookstore similarity search based on P-Rank
WU Chun-xu · Jisuanji gongcheng yu sheji · 2015
To increase the efficiency of algorithms on online bookstore's similarity search,and reduce time and space cost to adapt to large information network,ProductP-Rank,an optimized similarity search method,was proposed based on the basic idea of P-Rank.The past algorithms for similarity search were analyzed and discussed and the accuracy and complexity problems in similarity search were pointed out.By building the customer-product network according to the co-purchasing relationship,for a given query,the 2-hop similarity matrix between query and each item was computed based on the pre-computed 1-hop similarity matrix.Experimental results show the space cost and pre-computation time cost of ProductP-Rank were evidently less than that of P-Rank with little effectiveness loss and low online-query time cost.