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US 11,900,106 B2Granted
Personalized patch notes based on software usage
AssigneeInternational Business Machines Corporation
InventorsZachary A. Silverstein, Jacob Ryan Jepperson, Spencer Thomas Reynolds, Jeremy R. Fox
Life of this patent
Estimating the term…
Abstract
Aspects of the present disclosure relate to personalized software release note generation. Software usage of a user with respect to a software application can be tracked. Software release notes of the software application can be analyzed with respect to the software usage. Personalized software release notes can be generated for the user based on the analyzing. The personalized software release notes can be presented to the user.
Claims14
A method comprising:
- tracking software usage of a user with respect to a software application, wherein tracking software usage of the user with respect to the software application includes:
- identifying a number of interactions with software features of the software application over a first time period;
- determining a subset of software features of the software application that have a number of interactions exceeding a threshold number of interactions;
- analyzing software release notes of the software application with respect to the software usage by identifying a set of keywords corresponding to the subset of software features and searching for the set of keywords corresponding to the subset of software features within the software release notes;
- generating personalized software release notes for the user by extracting text associated with the set of keywords from the software release notes and integrating the extracted text into the personalized software release notes;
- presenting the personalized software release notes to the user;
- receiving user feedback regarding the user's satisfaction with the personalized software release notes;
- inputting the user feedback into a machine learning algorithm configured to adjust the threshold number of interactions based on the user feedback;
- generating, by the machine learning algorithm, an update to the threshold number of interactions based on the user feedback;
- and
- updating the threshold number of interactions based on the update to receive a second threshold number of interactions.
8 more elements
A system comprising:
- one or more processors;
- and
- one or more computer-readable storage media collectively storing program instructions which, when executed by the one or more processors, are configured to cause the one or more processors to perform a method comprising:
- tracking software usage of a user with respect to a software application, wherein tracking software usage of the user with respect to the software application includes:
- identifying a number of interactions with software features of the software application over a first time period;
- determining a subset of software features of the software application that have a number of interactions exceeding a threshold number of interactions;
- analyzing software release notes of the software application with respect to the software usage by identifying a set of keywords corresponding to the subset of software features and searching for the set of keywords corresponding to the subset of software features within the software release notes;
- generating personalized software release notes for the user by extracting text associated with the set of keywords from the software release notes and integrating the extracted text into the personalized software release notes;
- presenting the personalized software release notes to the user;
- receiving user feedback regarding the user's satisfaction with the personalized software release notes;
- inputting the user feedback into a machine learning algorithm configured to adjust the threshold number of interactions based on the user feedback;
- generating, by the machine learning algorithm, an update to the threshold number of interactions based on the user feedback;
- and
- updating the threshold number of interactions based on the update to receive a second threshold number of interactions.
11 more elements
A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising instructions configured to cause one or more processors to perform a method comprising:
- tracking software usage of a user with respect to a software application, wherein tracking software usage of the user with respect to the software application includes:
- identifying a number of interactions with software features of the software application over a first time period;
- determining a subset of software features of the software application that have a number of interactions exceeding a threshold number of interactions;
- analyzing software release notes of the software application with respect to the software usage by identifying a set of keywords corresponding to the subset of software features and searching for the set of keywords corresponding to the subset of software features within the software release notes;
- generating personalized software release notes for the user by extracting text associated with the set of keywords from the software release notes and integrating the extracted text into the personalized software release notes;
- presenting the personalized software release notes to the user;
- receiving user feedback regarding the user's satisfaction with the personalized software release notes;
- inputting the user feedback into a machine learning algorithm configured to adjust the threshold number of interactions based on the user feedback;
- generating, by the machine learning algorithm, an update to the threshold number of interactions based on the user feedback;
- and
- updating the threshold number of interactions based on the update to receive a second threshold number of interactions.
8 more elements
Dependencies are inferred from the claim text.