A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Agents that reduce work and information overload
Communications of the ACM
Nonmonotonic inference based on expectations
Artificial Intelligence
The nature of statistical learning theory
The nature of statistical learning theory
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Information flow: the logic of distributed systems
Information flow: the logic of distributed systems
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive Retrieval Agents: Internalizing Local Contextand Scaling up to the Web
Machine Learning - Special issue on information retrieval
A statistical learning learning model of text classification for support vector machines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Discovering information flow suing high dimensional conceptual space
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Application of aboutness to functional benchmarking in information retrieval
ACM Transactions on Information Systems (TOIS)
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Inferring query models by computing information flow
Proceedings of the eleventh international conference on Information and knowledge management
Amalthaea: An Evolving Multi-Agent Information Filtering and Discovery System for the WWW
Autonomous Agents and Multi-Agent Systems
Towards context sensitive information inference
Journal of the American Society for Information Science and Technology - Mathematical, logical, and formal methods in information retrieval
Context Sensitive Text Mining and Belief Revision for Adaptive Information Retrieval
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Unsupervised clustering for nontextual web document classification
Decision Support Systems
Revisions of knowledge systems using epistemic entrenchment
TARK '88 Proceedings of the 2nd conference on Theoretical aspects of reasoning about knowledge
To grow in wisdom: vannevar bush, information overload, and the life of leisure
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
An integrated two-stage model for intelligent information routing
Decision Support Systems
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Iterated theory base change: a computational model
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Extended Kalman Filter for wireless LAN based indoor positioning
Decision Support Systems
Using domain-specific knowledge in generalization error bounds for support vector machine learning
Decision Support Systems
A document classification and retrieval system for R&D in semiconductor industry - A hybrid approach
Expert Systems with Applications: An International Journal
Decision Support Systems
On strategies for imbalanced text classification using SVM: A comparative study
Decision Support Systems
Commercial Internet filters: Perils and opportunities
Decision Support Systems
A two-stage decision model for information filtering
Decision Support Systems
Agent and multi-agent applications to support distributed communities of practice: a short review
Autonomous Agents and Multi-Agent Systems
Extended information inference model for unsupervised categorization of web short texts
Journal of Information Science
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Effective decision making is based on accurate and timely information. However, human decision makers are often overwhelmed by the huge amount of electronic data these days. The main contribution of this paper is the development of effective information agents which can autonomously classify and filter incoming electronic data on behalf of their human users. The proposed information agents are innovative because they can quickly classify electronic documents solely based on the short titles of these documents. Moreover, supervised learning is not required to train the classification models of these agents. Document classification is based on information inference conducted over a high dimensional semantic information space. What is more, a belief revision mechanism continuously maintains a set of user preferred information categories and filter documents with respect to these categories. Preliminary experimental results show that our document classification and filtering mechanism outperforms the Support Vector Machines (SVM) model which is regarded as one of the best performing classifiers.