Processing

Please wait...

Settings

Settings

Goto Application

1. US20210026846 - Querying a data graph using natural language queries

Office
United States of America
Application Number 16949076
Application Date 13.10.2020
Publication Number 20210026846
Publication Date 28.01.2021
Grant Number 11403288
Grant Date 02.08.2022
Publication Kind B2
IPC
G06F 16/245
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
CPC
G06F 16/245
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
Applicants GOOGLE LLC
Inventors Amarnag Subramanya
Fernando Pereira
Ni Lao
John Blitzer
Rahul Gupta
Agents Brake Hughes Belermann LLP
Title
(EN) Querying a data graph using natural language queries
Abstract
(EN)

Implementations include systems and methods for querying a data graph. An example method includes receiving a machine learning module trained to produce a model with multiple features for a query, each feature representing a path in a data graph. The method also includes receiving a search query that includes a first search term, mapping the search query to the query, and mapping the first search term to a first entity in the data graph. The method may also include identifying a second entity in the data graph using the first entity and at least one of the multiple weighted features, and providing information relating to the second entity in a response to the search query. Some implementations may also include training the machine learning module by, for example, generating positive and negative training examples from an answer to a query.