scholarly journals Swarm Intelligence Based Optimization for Web Usage Mining in Recommender System

2013 ◽  
Vol 3 (2) ◽  
pp. 119-124 ◽  
Author(s):  
Manisha Sajwan ◽  
Kritika Acharya ◽  
Sanjay Bhargava
Keyword(s):  
Swarm Intelligence ◽  
Recommender System ◽  
Web Usage Mining ◽  
Web Usage

scholarly journals A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Anna Alphy ◽  
S. Prabakaran
Keyword(s):  
Collaborative Filtering ◽  
Swarm Intelligence ◽  
Foraging Behavior ◽  
Recommender System ◽  
Information Overload ◽  
Web Usage Mining ◽  
Dynamic Nature ◽  
Dynamic Behaviors ◽  
Web Usage ◽  
And Behavior

In modern days, to enrich e-business, the websites are personalized for each user by understanding their interests and behavior. The main challenges of online usage data are information overload and their dynamic nature. In this paper, to address these issues, a WebBluegillRecom-annealing dynamic recommender system that uses web usage mining techniques in tandem with software agents developed for providing dynamic recommendations to users that can be used for customizing a website is proposed. The proposed WebBluegillRecom-annealing dynamic recommender uses swarm intelligence from the foraging behavior of a bluegill fish. It overcomes the information overload by handling dynamic behaviors of users. Our dynamic recommender system was compared against traditional collaborative filtering systems. The results show that the proposed system has higher precision, coverage,F1measure, and scalability than the traditional collaborative filtering systems. Moreover, the recommendations given by our system overcome the overspecialization problem by including variety in recommendations.

scholarly journals Constructing a web recommender system using web usage mining and user’s profiles

2014 ◽  
pp. 2479-2486 ◽  
Author(s):  
T. Mombeini ◽  
A. Harounabadi ◽  
J. Rezaeian Sheshdeh
Keyword(s):  
Recommender System ◽  
Web Usage Mining ◽  
Web Usage

A personalized recommender system based on web usage mining and decision tree induction

2002 ◽  
Vol 23 (3) ◽  
pp. 329-342 ◽  
Author(s):  
Yoon Ho Cho ◽  
Jae Kyeong Kim ◽  
Soung Hie Kim
Keyword(s):  
Decision Tree ◽  
Recommender System ◽  
Web Usage Mining ◽  
Web Usage ◽  
Decision Tree Induction ◽  
Personalized Recommender System

scholarly journals Optimal Biclustering using Hybrid Swarm Intelligence for Web usage Mining

2019 ◽  
Vol 8 (2) ◽  
pp. 6392-6395
Keyword(s):  
Swarm Intelligence ◽  
Web Usage Mining ◽  
Web Pages ◽  
Crossover Operator ◽  
Critical Research ◽  
Hybrid Swarm ◽  
Swarm Optimization ◽  
Clustering Techniques ◽  
Web Usage ◽  
Browsing Behavior

Web usage mining is used to analyze the user browsing behavior among the web pages which can be further utilized in other applications like recommender system, personalized web pages, providing insight for better business functionality. Since this type of mining does not only depends on the user or web pages, conventional clustering techniques may not suit very well for the analysis. Biclustering techniques are used to discover the subset in the form of submatrices as objects and attributes of objects are considered symmetrically. Finding optimal biclusters is a critical research issue. This research proposes a hybrid swarm intelligence-based method having Particle Swarm Optimization combined with Leader Clustering method along with Uniform Crossover operator. The experimental study shows that the proposed method performs well than traditional biclustering techniques in terms of evaluation metrics.

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