【Web挖掘】PageRank and Interaction Information Retrieval

【文件属性】：
文件名称：【Web挖掘】PageRank and Interaction Information Retrieval
文件大小：103KB
文件格式：PDF
更新时间：2018-05-28 02:58:07
pagerank web挖掘 Web挖掘相关文档 The PageRank method is used by the Google Web search engine to compute the importance of Web pages. Two different views have been developed for the interpretation of the PageRank method and values: (a) stochastic (random surfer): the PageRank values can be conceived as the steady-state distribution of a Markov chain, and (b) algebraic: the PageRank values form the eigenvector corresponding to eigenvalue 1 of the Web link matrix. The Interaction Information Retrieval (I2R) method is a nonclassical information retrieval paradigm, which represents a connectionist approach based on dynamic systems. In the present paper, a different interpretation of PageRank is proposed, namely, a dynamic systems viewpoint, by showing that the PageRank method can be formally interpreted as a particular case of the Interaction Information Retrieval method; and thus, the PageRank values may be interpreted as neutral equilibrium points of the Web.