Abstract
Log files and reports describing outages and bugs include a number of free-form text fields that include crucial information about the outages or bugs. However, such information may often be lost because it does not have a defined structure. For such information to become useful, developers often manually label the data to find patterns. This is a labor intensive process. This disclosure describes natural language processing (NLP) techniques to automatically extract and store relevant structured information from free-form text fields. Such information, once in structured format, can be used to analyze the data and identify trends. Free-form information is recast in structured format, and insights obtained therefrom can be used to analyze the data and to identify trends such as common types of bugs, affected users, critical components or binaries, etc.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Kakkar, Prerna; Nagpal, Shrey; Sharma, Shubham; and Paul, Souvik, "Keyword Extraction and Analysis from Free-form Text", Technical Disclosure Commons, (November 02, 2023)
https://www.tdcommons.org/dpubs_series/6382