Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Fab: content-based, collaborative recommendation
Communications of the ACM
Pruning and summarizing the discovered associations
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining navigation history for recommendation
Proceedings of the 5th international conference on Intelligent user interfaces
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Data Mining and Knowledge Discovery
User Modeling for Personalized City Tours
Artificial Intelligence Review
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Fuzzy logic methods in recommender systems
Fuzzy Sets and Systems - Theme: Multicriteria decision
MMAC: A New Multi-Class, Multi-Label Associative Classification Approach
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Communications of the ACM - The Blogosphere
On a Hybrid Rule Based Recommender System
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Fuzzy methods for case-based recommendation and decision support
Journal of Intelligent Information Systems
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Information Sciences: an International Journal
Clustering people according to their preference criteria
Expert Systems with Applications: An International Journal
A recommender system using GA K-means clustering in an online shopping market
Expert Systems with Applications: An International Journal
A collaborative recommender system based on probabilistic inference from fuzzy observations
Fuzzy Sets and Systems
Adaptive Tourism Modeling and Socialization System
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Expert Systems with Applications: An International Journal
Recommender system based on workflow
Decision Support Systems
Integrating web mining and neural network for personalized e-commerce automatic service
Expert Systems with Applications: An International Journal
Collaborative filtering with temporal dynamics
Communications of the ACM
Distributed recommender for peer-to-peer knowledge sharing
Information Sciences: an International Journal
International Journal of Approximate Reasoning
Collaborative user modeling with user-generated tags for social recommender systems
Expert Systems with Applications: An International Journal
Making use of associative classifiers in order to alleviate typical drawbacks in recommender systems
Expert Systems with Applications: An International Journal
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Using quantitative association rules in collaborative filtering
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
A collaborative filtering approach to mitigate the new user cold start problem
Knowledge-Based Systems
Applying fuzzy logic to recommend consumer electronics
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
Advances in Clustering Collaborative Filtering by means of Fuzzy C-means and trust
Expert Systems with Applications: An International Journal
Leveraging clustering approaches to solve the gray-sheep users problem in recommender systems
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.