Invention Grant
- Patent Title: Significant correlation framework for command translation
-
Application No.: US16457599Application Date: 2019-06-28
-
Publication No.: US11281862B2Publication Date: 2022-03-22
- Inventor: Aavishkar Bharara , Anbarasu Ayyasami , Anil Rao Arun , Ramya K S , Deepanshi Katoch , Shrijan Shrivastav , Ankita Prabhu , Ashwani Kumar Luhaniwal
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Klarquist Sparkman, LLP
- Priority: IN201911017698 20190503
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F40/30 ; G06F40/205 ; G10L15/18 ; G10L15/22

Abstract:
A significant correlation framework is provided herein for translating input commands to intents. The input commands may be natural language commands, received from a variety of input channels, which may be translated to intents or other runtime-bindable execution objects. The significant correlation framework may use interpreter nodes for translating the input commands by calculating the strength of correlation between an input command and an intent. The significant correlation framework may analyze the sequence of intents or the timing of translated intents to enhance the accuracy of the translation. The significant correlation framework may maintain a history of command translations, and may compare current translations against the history to improve accuracy of the translations. The significant correlation framework may switch between a depth-first mapping method and a breadth-first mapping method. Depth-first mapping may translate commands through a single interpreter node. Breadth-first mapping may translate commands using multiple interpreter nodes.
Public/Granted literature
- US20200349228A1 SIGNIFICANT CORRELATION FRAMEWORK FOR COMMAND TRANSLATION Public/Granted day:2020-11-05
Information query