- Patent Title: Using ontological distance to measure unexpectedness of correlation
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Application No.: US15158849Application Date: 2016-05-19
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Publication No.: US10580017B2Publication Date: 2020-03-03
- Inventor: Alireza Pourshahid , Vinay N. Wadhwa , Graham A. Watts , Qing Wei
- 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: Winstead PC
- Agent Robert A. Voigt, Jr.
- Main IPC: G06Q30/02
- IPC: G06Q30/02

Abstract:
A method, system and computer program product for evaluating the interestingness of correlated data. The fields of a dataset are classified by tagging the fields in terms of real world concepts. A correlation analysis on the dataset is performed to generate a correlation coefficient for each pair of fields of correlated data items. An “ontological distance” between the tagged concepts for each pair of fields of correlated data items represented as nodes in the ontology is determined. A score is generated indicating an interestingness of correlation for each pair of fields of correlated data items based on the correlation coefficient and the ontological distance between the tagged concepts for each pair of fields of correlated data items. By utilizing the ontological distance with the correlation analysis to determine the interestingness of correlation, correlations that may not be obvious to users and unexpectedly correlated may be identified.
Public/Granted literature
- US20170116623A1 USING ONTOLOGICAL DISTANCE TO MEASURE UNEXPECTEDNESS OF CORRELATION Public/Granted day:2017-04-27
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