Invention Grant
- Patent Title: Context-based recommendation system for feature search
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Application No.: US16876624Application Date: 2020-05-18
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Publication No.: US12032607B2Publication Date: 2024-07-09
- Inventor: Sudhir Tubegere Shankaranarayana , Sreenivas Ramaswamy , Sachin Tripathi , Reetesh Mukul , Mayuri Jain , Bhakti Ramnani
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06F16/33
- IPC: G06F16/33 ; G06F16/332 ; G06F40/284 ; G06N20/00

Abstract:
A context-based recommendation system for feature search automatically identifies features of a feature-rich system (e.g., an application) based on the program code of the feature-rich system and additional data corresponding to the feature-rich system. A code workflow graph describing workflows in the program code is generated. Various data corresponding to the feature-rich system, such as help data, analytics data, social media data, and so forth is obtained. The code workflow graph and the data are analyzed to identify sentences in the workflow. These sentences are used to a train machine learning system to generate one or more recommendations. In response to a user query, the machine learning system generates and outputs as recommendations workflows identified based on the user query.
Public/Granted literature
- US20210357440A1 Context-based Recommendation System for Feature Search Public/Granted day:2021-11-18
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