Title Of Paper:
 
 
A Recommender System for Web Mining using SFLA-K-harmonic Mean
Author's Name :  Hamidhe jashn, Mashallah AbbasiDezfouli
KeyWords:  Web usage mining, K-harmonic means, Shuffled frog-leaping algorithm, Particle swarm optimization
Pages:  13 -19
Volume: 4
Issue: 7
Year: 2016
Abstract:
 

Discovering the knowledge hidden in the users' interactions on the Web is one of the important tools of Web Usage Mining. This paper proposes a method based on the Usage Mining of web-server records. The clustering algorithm is presented in order to produce the users' movement patterns and this clustering algorithm is a combination of based K-harmonic means clustering algorithm and Shuffled frog leaping algorithm. After creating the movement patterns, the recommender system offers a list of user's favorite pages which have not been read by user until now. The recommender system works based on a combination of neural network and particle optimization algorithm. The results of research indicate that the proposed algorithm has higher precision and less time than the other compared algorithms.

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