Determining the Similarity of Web Pages based on Learning Automata and Probabilistic Grammar

As the number of web pages increases, search for useful information by users on web sites will become more significant. By determining the similarity of web pages, search quality can beimproved; hence, users can easily find their relevant information. In this paper, distributed learning automata and probabilisticgrammar were used to propose a new hybrid algorithm in order to specify the similarity of web pages by means of web usagedata. In the proposed algorithm, a Learning Automata (LA) for each web page is assigned which its function is to evaluate association rules extracted by hypertext system. This learningprocess continues until the similarity of web pages are determined. Experimental results demonstrate the efficiency of the proposed algorithm over other existing techniques

Keywords:

Web Mining , Association Rules , Learning Automata , Distributed Learning Automata , Hypertext Probabilistic Grammar