Test classification system and method

Image analysis – Pattern recognition – Classification

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382224, 382228, 382229, 382230, 345440, G06K 962, G06K 972, G06K 974

Patent

active

061379115

ABSTRACT:
Documents are classified into one or more clusters corresponding to predefined classification categories by building a knowledge base comprising matrices of vectors which indicate the significance of terms within a corpus of text formed by the documents and classified in the knowledge base to each cluster. The significance of terms is determined assuming a standard normal probability distribution, and terms are determined to be significant to a cluster if their probability of occurrence being due to chance is low. For each cluster, statistical signatures comprising sums of weighted products and intersections of cluster terms to corpus terms are generated and used as discriminators for classifying documents. The knowledge base is built using prefix and suffix lexical rules which are context-sensitive and applied selectively to improve the accuracy and precision of classification.

REFERENCES:
patent: 4754489 (1988-06-01), Bokser
patent: 4876731 (1989-10-01), Loris et al.
patent: 5062143 (1991-10-01), Schmitt
patent: 5075896 (1991-12-01), Wilcox
patent: 5151950 (1992-09-01), Hullender
patent: 5625767 (1997-04-01), Bartell et al.
patent: 5703964 (1997-12-01), Menon et al.
patent: 5751850 (1998-05-01), Rindtorff
patent: 5818952 (1998-10-01), Takenouchi et al.
"An Association Based Method for Automatic Indexing with a Controlled Vocabulary", Christian Plaunt and Barbara A. Norgard, Oct. 2, 1995.
"Inductive Text Classification for Medical Applications", Wendy Lehnert, Stephen Soderland, David Aronow, Fangfang Feng, Avionoam Shmueli, Journal for Experimental and Theoretical Artificial Intelligence, 1995.
"Automated Classification of Encounter Notes in a Computer Based Medical Record", D.B. Aronow, S. Soderland, J.M. Ponte, Feng F., W.B. Croft, W.G. Lehnert, Undated.
"Suggesting Terms for Query Expansion in a Medical Information Retrieval System", Morris Hirsch, David Aronow, Undated.
"A Sequential Algorithm for Training Text Classifiers", David D. Lewis, William A. Gale, Jul. 24, 1994.
"Similarity between Words Computed by Spreading Activation on an English Dictionary", Hideki Kozima, Teiji Furugori, Undated.
"Training Algorithms for Linear Text Classifiers", David D. Lewis, Robert E. Schapire, James P. Callan, Ron Papka, Undated.
"Information Extraction as a Basis for High-Precision Text Classification", Ellen Riloff, Wendy Lehnert, ACM Transactions on Information Systems, vol. 12, No. 3, pp. 296-333, Jul. 1994.
"Combining Classifiers in Text Categorization", Leah S. Larkey, W. Bruce Croft, Mar. 20, 1996.
"Viewing Morphology as an Inference Process", Robert Krovetz, Undated.
"Corpus-Specific Stemming using Word Form Co-occurrence", W. Bruce Croft, Jinxi Xu, Undated.
"Automatic Assignment of ICD9 Codes to Discharge Summaries", Leah S. Larkey, W. Bruce Croft, Undated.
"Similarity-Based Estimation of Word Cooccurrence Probabilities", Ido Dagan, Fernando Pereira, Mar. 27, 1996.
"Context-Sensitive Measurement of Word Distance by Adaptive Scaling of a Semantic Space", Hideki Kozima, Akira Ito, Undated.
"Structural Tags, Annealing and Automatic Word Classification", J. McMahon, F.J. Smith, Oct. 25, 1994.
Schutze, et al "A Cooccurrence-Based Thesaurus and Two Applications to Information Retrieval," pp. 307-318, Feb. 1996.

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