Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Journal of the American Society for Information Science
Fab: content-based, collaborative recommendation
Communications of the ACM
AGENTS '98 Proceedings of the second international conference on Autonomous agents
A learning agent for wireless news access
Proceedings of the 5th international conference on Intelligent user interfaces
Developing recommendation services for a digital library with uncertain and changing data
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
A graph-based recommender system for digital library
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Novelty and redundancy detection in adaptive filtering
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
Enhancing digital libraries with TechLens+
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
IEEE Transactions on Knowledge and Data Engineering
Document similarity based on concept tree distance
Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
Technical paper recommendation: a study in combining multiple information sources
Journal of Artificial Intelligence Research
Latent class models for collaborative filtering
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
User profiles for personalized information access
The adaptive web
Collaborative filtering recommender systems
The adaptive web
Content-based recommendation systems
The adaptive web
Citation recommendation without author supervision
Proceedings of the fourth ACM international conference on Web search and data mining
A source independent framework for research paper recommendation
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Recommending academic papers via users' reading purposes
Proceedings of the sixth ACM conference on Recommender systems
Introducing Docear's research paper recommender system
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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The information explosion in today's electronic world has created the need for information filtering techniques that help users filter out extraneous content to identify the right information they need to make important decisions. Recommender systems are one approach to this problem, based on presenting potential items of interest to a user rather than requiring the user to go looking for them. In this paper, we propose a recommender system that recommends research papers of potential interest to authors known to the CiteSeer database. For each author participating in the study, we create a user profile based on their previously published papers. Based on similarities between the user profile and profiles for documents in the collection, additional papers are recommended to the author. We introduce a novel way of representing the user profiles as trees of concepts and an algorithm for computing the similarity between the user profiles and document profiles using a tree-edit distance measure. Experiments with a group of volunteers show that our concept-based algorithm provides better recommendations than a traditional vector-space model based technique.