Journal of Software Engineering and Applications

Journal of Software Engineering and Applications

ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.org/journal/jsea
E-mail: jsea@scirp.org
"A Hybrid Web Recommendation System Based on the Improved Association Rule Mining Algorithm"
written by Ujwala H. Wanaskar, Sheetal R. Vij, Debajyoti Mukhopadhyay,
published by Journal of Software Engineering and Applications, Vol.6 No.8, 2013
has been cited by the following article(s):
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[3] Time-Aware CF and Temporal Association Rule-Based Personalized Hybrid Recommender System
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[4] Recommendation System Based on Semantic Web
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[5] Recommendation System Using Machine Learning
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[6] A Web Extraction Browsing Scheme for Time-Critical Specific URLs Fetching
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[7] A Survey of Recommendation Systems
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[8] Product Recommendation using Machine Learning Algorithm-A Better Appoarch
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[9] HYBRID HAVERSINE-GENETIC GEOGRAPHICAL MODELLING FOR AN OPTIMAL WEB SERVICE SELECTION/RECOMMENDATION.
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[10] A novel approach on Particle Agent Swarm Optimization (PASO) in semantic mining for web page recommender system of multimedia data: a health care perspective
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[11] Collaborative filtering recommendation algorithm towards intelligent community.
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[12] Predicting the degree of film transmission based on deep learning
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[13] Hybridizing association rules with adaptive weighted decision fusion for personal credit assessment
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[14] A Survey of Recommender Systems and Geographical Recommendation Techniques
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[15] F-PNWAR: Fuzzy-based Positive and Negative Weighted Association Rule Mining Algorithm
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[16] An Improved Business Service Suggestion Through SCHR Approach
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[17] Collaborative filtering recommendation algorithm towards intelligent community
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[18] Système de recherche d'information étendue basé sur une projection multi-espaces
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[19] Personalized web page recommendation using case-based clustering and weighted association rule mining
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[20] Data Mining of University Library Management Based on Improved Collaborative Filtering Association Rules Algorithm
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[21] CR-IIA: Collaborative Recommendation Algorithm Based on Implicit Item Associations
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[22] COLLABORATIVE RECOMMENDERATION BASED ON STATISTICAL IMPLICATION RULES
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[23] 협업 필터링 및 하이브리드 필터링을 이용한 동종 브랜드 판매 매장間 취급 SKU 추천 시스템
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[24] Machine Learning Algorithms for Recommender System-a comparative analysis
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[25] Design of Open Content Social Learning based on the Activities of Learner and Similar Learners
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[26] Machine Learning Algorithms for Recommender System–A Comparative Analysis
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[27] Research Article Application of Association Rule Mining Algorithm in Logistics Information System Design
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[28] Machine Learing Algorithms for Recommender System–a comparative analysis
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[29] Jiaxin Wang
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[30] SKU recommender system for retail stores that carry identical brands using collaborative filtering and hybrid filtering
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[31] Personal Information Prediction Based on Movie Rating Data
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[32] Design of Open Content Social Learning that Increases Learning Efficiency and Engagement Based on Open Pedagogy
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[33] A novel hybrid based recommendation system based on clustering and association mining
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[34] 基于柯西分布量子粒子群的混合推荐算法
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[35] A Public Cloud based SOA Workflow for Machine Learning based Recommendation Algorithms
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[36] A hybrid recommendation algorithm based on time factor
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[37] UBS: A Novel News Recommendation System Based on User Behavior Sequence
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[38] AUTOMATED RECOMMENDATION OF INFORMATION TO THE MEDIA BY THE IMPLEMENTATION OF WEB SEARCHING TECHNIQUE
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[39] A Well-Built Hybrid Recommender System for Agricultural Products in Benue State of Nigeria
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[40] Recommendation based on clustering and association rules
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[41] Precomputed Clustering for Movie Recommendation System in Real Time
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[42] Challenges in context-aware mobile language learning: the MASELTOV approach
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[43] A Survey of Various Hybrid based Recommendation Method
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