Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Natural language understanding for information-filtering systems
Communications of the ACM - Special issue on information filtering
Knowledge-based assistance for accessing large, poorly structured information spaces
Knowledge-based assistance for accessing large, poorly structured information spaces
Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
WordNet: a lexical database for English
Communications of the ACM
Conceptual Information Retrieval: A Case Study in Adaptive Partial Parsing
Conceptual Information Retrieval: A Case Study in Adaptive Partial Parsing
Intelligent information filtering via hybrid techniques: hill climbing, case-based reasoning, index patterns, and genetic algorithms
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Supporting situated actions in high volume conversational data situations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The InfoFinder Agent: Learning User Interests through Heuristic Phrase Extraction
IEEE Expert: Intelligent Systems and Their Applications
Improving text categorization using the importance of sentences
Information Processing and Management: an International Journal
Automatic text categorization using the importance of sentences
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Local search: A guide for the information retrieval practitioner
Information Processing and Management: an International Journal
Fuzzy induction in dynamic user profiling for information filtering
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
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As the size of the Internet increases, the amount of data available to users has dramatically risen, resulting in an information overload for users. This work involved the creation of an intelligent information news filtering system named INFOS (Intelligent News Filtering Organizational System) to reduce the user's search burden by automatically eliminating Usenet news articles predicted to be irrelevant. These predictions are learned automatically by adapting an internal user model that is based upon features taken from articles and collaborative features derived from other users. The features are manipulated through keyword-based techniques and knowledge-based techniques to perform the actual filtering. Knowledge-based systems have the advantage of analyzing input text in detail, but at the cost of computational complexity and the difficulty of scaling up to large domains. In contrast, statistical and keyword approaches scale up readily but result in a shallower understanding of the input. A hybrid system integrating both approaches improves accuracy over keyword approaches, supports domain knowledge, and retains scalability. The system would be enhanced by more robust word disambiguation.