Patent · US Active

Cognitive feature analytics

US9916158B2 · kind B2 · utility

1Cited by
1References
14Claims
0Family size

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Key dates

Filing dateJul 20, 2016
Grant dateMar 13, 2018
Priority date
Expiry dateSep 1, 2036

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06F8/71
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A system and method to build feature evolution models for existing applications (“apps”) in the market based on open app data repositories). A feature evolution model of an app depicts the app name, its historical versions (historical version labels, release timestamps of each version), rating values of each version, and structured features (e.g., umbrella features and low-level features) each version introduces, improves or deletes. There is further extracted from the app description and release logs the app name, historical version labels, release timestamps, use the rating info of the app to extract and assign rating values for each version of the app, and apply NLP techniques and source code analysis techniques to extract “structured features” of the app through analyzing the app description, the release logs, and corresponding source code revisions of the app. Upon the built feature evolution models, various feature insights may be easily extracted and generated.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.