Invention Grant
- Patent Title: Phenomenological semantic distance from latent dirichlet allocations (LDA) classification
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Application No.: US15225445Application Date: 2016-08-01
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Publication No.: US10229184B2Publication Date: 2019-03-12
- Inventor: Jennifer A. English , Malous M. Kossarian , Charles E. McManis, Jr. , Douglas A. Smith
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Pepper Hamilton LLP
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.
Public/Granted literature
- US20180032600A1 PHENOMENOLOGICAL SEMANTIC DISTANCE FROM LATENT DIRICHLET ALLOCATIONS (LDA) CLASSIFICATION Public/Granted day:2018-02-01
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