Invention Grant
- Patent Title: Compressing multi-attribute vector into a single eigenvalue for ranking subject matter experts
-
Application No.: US17121806Application Date: 2020-12-15
-
Publication No.: US11630663B2Publication Date: 2023-04-18
- Inventor: Andrew C. M. Hicks , Robert Peter Catalano , Tyler Vezio Rimaldi , Daniel Nicolas Gisolfi
- 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: Cantor Colburn LLP
- Agent Teddi Maranzano
- Main IPC: G06F8/77
- IPC: G06F8/77 ; G06F8/71 ; G06T11/20

Abstract:
Aspects of the invention include determining, by a processor, a code segment of a computer code, analyzing the code segment to determine one or more other code segments associated with the code segment, determining a set of subject matter experts (SMEs) associated with the code segment and the one or more other code segments, obtaining SME data for each SME in the set of SMEs, wherein the SME data comprises a set of attributes associated with the SME, generating, by the processor, a graphical representation of the set of attributes for each SME in the set of SMEs, transforming the graphical representations into an eigenvectors and eigenvalues, and ranking the SMEs based on their associated eigenvectors and eigenvalues.
Public/Granted literature
- US20220188105A1 COMPRESSING MULTI-ATTRIBUTE VECTOR INTO A SINGLE EIGENVALUE FOR RANKING SUBJECT MATTER EXPERTS Public/Granted day:2022-06-16
Information query