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Message Analysis for the Recommendation of Contact Persons within Defined Subject Fields
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Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Extraction Positive and Negative Keywords for Web Communities
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Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001
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Handbook of massive data sets
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Information Processing Letters
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IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Algorithm 844: Computing sparse reduced-rank approximations to sparse matrices
ACM Transactions on Mathematical Software (TOMS)
Subproblem optimization by gene correlation with singular value decomposition
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Selforganizing classification on the Reuters news corpus
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A patent document retrieval system addressing both semantic and syntactic properties
PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
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Information Processing and Management: an International Journal
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Access Structures for Angular Similarity Queries
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Fast computation of low-rank matrix approximations
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HOTOS'03 Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9
A measure theoretic approach to information retrieval
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A comparative analysis on the bisecting K-means and the PDDP clustering algorithms
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SemreX: Efficient search in a semantic overlay for literature retrieval
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CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
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Pattern Recognition Letters
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Affiliation dynamics with an application to movie-actor biographies
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International Journal of Communication Systems
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Pattern Recognition Letters
| Hi-index | 0.06 |
The evolution of digital libraries and the Internet has dramatically transformed the processing, storage, and retrieval of information. Efforts to digitize text, images, video, and audio now consume a substantial portion of both academic and industrial activity. Even when there is no shortage of textual materials on a particular topic, procedures for indexing or extracting the knowledge or conceptual information contained in them can be lacking. Recently developed information retrieval technologies are based on the concept of a vector space. Data are modeled as a matrix, and a user's query of the database is represented as a vector. Relevant documents in the database are then identified via simple vector operations. Orthogonal factorizations of the matrix provide mechanisms for handling uncertainty in the database itself. The purpose of this paper is to show how such fundamental mathematical concepts from linear algebra can be used to manage and index large text collections.