Invention Grant
- Patent Title: Model-based semantic text searching
-
Application No.: US16849885Application Date: 2020-04-15
-
Publication No.: US11567981B2Publication Date: 2023-01-31
- Inventor: Trung Bui , Yu Gong , Tushar Dublish , Sasha Spala , Sachin Soni , Nicholas Miller , Joon Kim , Franck Dernoncourt , Carl Dockhorn , Ajinkya Kale
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Nicholson De Vos Webster & Elliot LLP
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06F16/33 ; G06N20/00 ; G06N5/04

Abstract:
Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.
Public/Granted literature
- US20210326371A1 MODEL-BASED SEMANTIC TEXT SEARCHING Public/Granted day:2021-10-21
Information query