Communications of the ACM
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
ELFI: information brokering for the domain of research funding
TNC'98 Proceedings of the TERENA networking conference '98 on Towards networking and services in the year 2001
A hybrid user model for news story classification
UM '99 Proceedings of the seventh international conference on User modeling
Machine learning and knowledge representation in the LaboUr approach to user modeling
UM '99 Proceedings of the seventh international conference on User modeling
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Capturing knowledge of user preferences: ontologies in recommender systems
Proceedings of the 1st international conference on Knowledge capture
User Modeling and User-Adapted Interaction
How to Learn More about Users from Implicit Observations
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
An adaptive system for the personalized access to news
AI Communications
Proceedings of the 2007 ACM symposium on Applied computing
Proceedings of the 2008 ACM conference on Recommender systems
Tag-based user modeling for social multi-device adaptive guides
User Modeling and User-Adapted Interaction
Pervasive Web News Recommendation for Visually Impaired People
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
User modeling in adaptive audio-augmented museum environments
UM'03 Proceedings of the 9th international conference on User modeling
Context-awareness in user modelling: requirements analysis for a case-based reasoning application
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
User preference modeling from positive contents for personalized recommendation
DS'07 Proceedings of the 10th international conference on Discovery science
Modeling and learning user profiles for personalized content service
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
SWAMI: searching the web using agents with mobility and intelligence
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Collaborative user modeling for enhanced content filtering in recommender systems
Decision Support Systems
Towards effective course-based recommendations for public tenders
International Journal of Knowledge and Web Intelligence
Hi-index | 0.00 |
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that need training input to acquire a user interest profile are used. Such methods typically need positive and negative evidence of the user's interests. To obtain both kinds of evidence, many systems make users rate relevant objects explicitly. Others merely observe the user's behavior, which fairly obviously yields positive evidence; in order to be able to apply the standard learning methods, these systems mostly use heuristics that attempt to find also negative evidence in observed behavior.In this paper, we present several approaches to learning interest profiles from positive evidence only, as it is contained in observed user behavior. Thus, both the problem of interrupting the user for ratings and the problem of somewhat artificially determining negative evidence are avoided.The learning approaches were developed and tested in the context of the Web-based ELFI information system. It is in real use by more than 1000 people. We give a brief sketch of ELFI and describe the experiments we made based on ELFI usage logs to evaluate the different proposed methods.