Annual review of information science and technology, vol. 22
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Algorithms in C
Information retrieval
Relevance feedback and other query modification techniques
Information retrieval
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
SIGIR94 17th Annual International ACM SIGIR Conference on Research & Development in Information Retrieval
Improving text retrieval for the routing problem using latent semantic indexing
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The effect of adding relevance information in a relevance feedback environment
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Synthetic workload performance analysis of incremental updates
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Document filtering for fast ranking
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The MG retrieval system: compressing for space and speed
Communications of the ACM
In situ generation of compressed inverted files
Journal of the American Society for Information Science
Fast evaluation of structured queries for information retrieval
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Self-indexing inverted files for fast text retrieval
ACM Transactions on Information Systems (TOIS)
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Extended Boolean information retrieval
Communications of the ACM
Index Structures for Information Filtering Under the Vector Space Model
Proceedings of the Tenth International Conference on Data Engineering
Learning while filtering documents
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Functional Properties of Information Filtering
Proceedings of the 27th International Conference on Very Large Data Bases
A multi-criteria content-based filtering system
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Information filtering and query indexing for an information retrieval model
ACM Transactions on Information Systems (TOIS)
DELOS'07 Proceedings of the 1st international conference on Digital libraries: research and development
The gist of everything new: personalized top-k processing over web 2.0 streams
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A flexible news filtering model exploiting a hierarchical fuzzy categorization
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
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A high performance information filtering system has three mainrequirements: it must be effective in supplying users with usefulinformation, it must do so in a timely fashion, and it must be ableto handle a large throughput of information and a large number ofuser profiles efficiently. These three requirements pose adifficult problem, and to our knowledge no existing system iscapable of meeting all three. In this paper we describe a systemwhich combines a number of techniques from other informationretrieval and filtering systems, and is capable of providing highperformance on a typical workstation platform. We provide estimatesof computing resource usage, and show that our system is alsoscalable.