Intelligent information-sharing systems
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Index Structures for Information Filtering Under the Vector Space Model
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ACM SIGMOD Record
Document filtering with inference networks
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Incremental relevance feedback for information filtering
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A framework for scalable dissemination-based systems
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Exploiting enterprise models for the automatic distribution of corporate information
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Supporting situated actions in high volume conversational data situations
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Internet scrapbook: automating Web browsing tasks by demonstration
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Learning while filtering documents
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GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
Task-based information management
ACM Computing Surveys (CSUR)
The SIFT information dissemination system
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Using star clusters for filtering
Proceedings of the ninth international conference on Information and knowledge management
WebCQ-detecting and delivering information changes on the web
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Effective access to large audiovisual assets based on user preferences
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Hermes: a notification service for digital libraries
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Personalized web search by mapping user queries to categories
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Homogeneous Agent-Based Distributed Information Filtering
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User Modeling and User-Adapted Interaction
Mobile Computing and Databases-A Survey
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Continual Queries for Internet Scale Event-Driven Information Delivery
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A Statistical Method for Estimating the Usefulness of Text Databases
IEEE Transactions on Knowledge and Data Engineering
A Taxonomy of Recommender Agents on theInternet
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Agent-based intelligent information dissemination in dynamically changing environments
Intelligent agents and their applications
Exploiting Versions for Handling Updates in Broadcast Disks
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Design and Implementation of a Distributed Crawler and Filtering Processor
NGITS '02 Proceedings of the 5th International Workshop on Next Generation Information Technologies and Systems
Dynamic Spatial Clustering for Intelligent Mobile Information Sharing and Dissemination
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
Research in Data Broadcast and Dissemination
AMCP '98 Proceedings of the First International Conference on Advanced Multimedia Content Processing
A personalized information dissemination system based on How-Net
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Ontology Based Personalized Search
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Enabling Personalized Recommendation on the Web Based on User Interests and Behaviors
RIDE '01 Proceedings of the 11th International Workshop on research Issues in Data Engineering
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Personalized Web Search For Improving Retrieval Effectiveness
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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ACSC '06 Proceedings of the 29th Australasian Computer Science Conference - Volume 48
Supporting mobile access to digital video archives without user queries
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USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
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UM '07 Proceedings of the 11th international conference on User Modeling
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SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
Adaptive classification of web documents to users interests
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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The dissemination model is becoming increasingly important in wide-area information system. In this model, the user subscribes to an information dissemination service by submitting profiles that describe his interests. He then passively receives new, filtered information. The Stanford Information Filtering Tool (SIFT) is a tool to help provide such service. It supports full-text filtering using well-known information retrieval models. The SIFT filtering engine implements novel indexing techniques, capable of processing large volumes of information against a large number of profiles. It runs on several major Unix platforms and is freely available to the public. In this paper we present SIFT's approach to user interest modeling and user-server communication. We demonstrate the processing capability of SIFT by describing a running server that disseminates USENET News. We present an empirical study of SIFT's performance, examining its main memory requirement and ability to scale with information volume and user population.