Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Improving text retrieval for the routing problem using latent semantic indexing
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Recommender systems for evaluating computer messages
Communications of the ACM
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
The order of things: activity-centered information access
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Mining navigation history for recommendation
Proceedings of the 5th international conference on Intelligent user interfaces
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Data mining: concepts and techniques
Data mining: concepts and techniques
A music recommendation system based on music data grouping and user interests
Proceedings of the tenth international conference on Information and knowledge management
On the recommending of citations for research papers
CSCW '02 Proceedings of the 2002 ACM conference on Computer supported cooperative work
Exploiting Hierarchy in Text Categorization
Information Retrieval
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Sparsity, scalability, and distribution in recommender systems
Sparsity, scalability, and distribution in recommender systems
An integrated approach for developing e-commerce applications
Expert Systems with Applications: An International Journal
Mining changes in customer buying behavior for collaborative recommendations
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Using text classification and multiple concepts to answer e-mails
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Seeding the survey and analysis of research literature with text mining
Expert Systems with Applications: An International Journal
Optimizing customer's selection for configurable product in B2C e-commerce application
Computers in Industry
Text classification based on multi-word with support vector machine
Knowledge-Based Systems
Context-aware system for proactive personalized service based on context history
Expert Systems with Applications: An International Journal
A hybrid of sequential rules and collaborative filtering for product recommendation
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Customer requirements mapping method based on association rules mining for mass customisation
International Journal of Computer Applications in Technology
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Developing an ontology-supported information integration and recommendation system for scholars
Expert Systems with Applications: An International Journal
Identifying influential reviewers for word-of-mouth marketing
Electronic Commerce Research and Applications
Intelligent product search with soft-boundary preference relaxation
Expert Systems with Applications: An International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
Web usage mining to improve the design of an e-commerce website: OrOliveSur.com
Expert Systems with Applications: An International Journal
Back-buy prediction based on TriFG
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Journal of Intelligent Manufacturing
Dynamic Pricing Strategies Between Online and Off-Line Retailers Based on Switching Costs
Journal of Electronic Commerce in Organizations
Hi-index | 12.06 |
It has been recognized that e-commerce and mass customization will emerge as a primary style of manufacturing. The main challenge for such a paradigm originates from difficulties in personalization - providing support for customers to find the most valuable products that match their heterogeneous needs. Traditional approaches to the personalization problem adopt pre-defined formats to describe the customer requirements. This always leads to distortion in eliciting requirement information and thus inaccurate recommendations. Knowledge discovery lends itself to dealing with semi-structured data and makes it possible to capture customer requirements more accurately. This paper proposes an associative classification-based recommendation system for personalization in B2C e-commerce applications. Knowledge discovery techniques are applied to support personalization according to an inner established model that anticipates customer heterogeneous requirements. The framework and methodology of the associative classification-based recommendation system have been addressed. The system analysis, design, and implementation issues in an Internet programming environment are presented. The feasibility of the proposed recommendation system has been validated with a prototype for personalization in mobile phone B2C e-commerce applications.