CLINICALLY RELEVANT MEDICAL CONCEPT CLUSTERING
First Claim
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1. A computer implemented method comprising:
- identifying, within at least one taxonomy, relations between taxonomy categories and concepts extracted from electronic content, wherein the relations represent semantic similarities for the concepts; and
clustering the concepts based on the identified relations within the at least one taxonomy.
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Abstract
The present invention embodiments are directed to methods, systems, and computer programs for identifying relations, within at least one taxonomy, between taxonomy categories and concepts extracted from electronic content. The relations represent semantic similarities for the concepts. The concepts are clustered based on the identified relations within the at least one taxonomy.
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Citations
20 Claims
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1. A computer implemented method comprising:
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identifying, within at least one taxonomy, relations between taxonomy categories and concepts extracted from electronic content, wherein the relations represent semantic similarities for the concepts; and clustering the concepts based on the identified relations within the at least one taxonomy. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer program product for clustering concepts extracted from electronic content, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
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identify, within at least one taxonomy, relations between taxonomy categories and the concepts extracted from the electronic content, wherein the relations represent semantic similarities for the concepts; and cluster the concepts based on the identified relations within the at least one taxonomy. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A system comprising:
at least one processor configured to; identify within at least one taxonomy, relations between taxonomy categories and concepts extracted from electronic content, wherein the relations represent semantic similarities for the concepts; and cluster the concepts based on the identified relations within the at least one taxonomy. - View Dependent Claims (18, 19, 20)
Specification