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To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS ...
The method used involves generation of different kinds of models. These include regression and rule models, piecewise linear models (model trees) and instance ...
To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS ...
Discover how web usage mining can predict user behavior and improve website design. Explore our advanced recommender system using LCS classification algorithm.
In the second experiment, prediction of the user next request has been performed by classification algorithm based on longest common subsequence (LCS).
A model for online predicting through web usage mining system is developed and a novel approach for classifying user navigation patterns to predict users' ...
In this paper we present architecture for integrating semantic information about the products with web log data and generate a list of recommended products by ...
This paper advanced the online recommender system by using a Longest Common Subsequence (LCS) classification algorithm to classify users' navigation pattern ...
The classification algorithm used is the Longest Common Subsequence (LCS), proposed by Jalali et al.[9]. The study divides the pattern discovery and analysis ...
In the second experiment, prediction of the user next request has been performed by classification algorithm based on longest common subsequence (LCS). 5.1.