US 11,853,902 B2
Developing event-specific provisional knowledge graphs
Victor Carbune, Zurich (CH); and Sandro Feuz, Zurich (CH)
Assigned to GOOGLE LLC, Mountain View, CA (US)
Filed by GOOGLE LLC, Mountain View, CA (US)
Filed on Jan. 11, 2022, as Appl. No. 17/572,903.
Application 17/572,903 is a continuation of application No. 16/622,555, granted, now 11,256,992, previously published as PCT/US2019/038940, filed on Jun. 25, 2019.
Prior Publication US 2022/0138591 A1, May 5, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/35 (2020.01); G06N 5/02 (2023.01); G06F 40/205 (2020.01); G06F 40/295 (2020.01); H04L 51/046 (2022.01)
CPC G06N 5/02 (2013.01) [G06F 40/205 (2020.01); G06F 40/295 (2020.01); G06F 40/35 (2020.01); H04L 51/046 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method implemented using one or more processors, comprising:
identifying a cluster of semantically-related textual snippets, composed by a plurality of users, that are transmitted over one or more computer networks;
based on the cluster of semantically-related textual snippets, newly detecting a developing event and identifying one or more entities associated with the newly-detected developing event, wherein one or more of the identified entities form part of a general-purpose knowledge graph that includes a plurality of entity nodes and a plurality of edges between the plurality of entity nodes, wherein the plurality of entity nodes of the general-purpose knowledge graph represent entities and the plurality of edges represent relationships between entities;
in response to newly detecting the developing event, and based on the identified one or more entities, constructing an event-specific provisional knowledge graph associated with the newly-detected developing event,
wherein the event-specific provisional knowledge graph shares one or more entity nodes with the general-purpose knowledge graph, and
wherein the event-specific provisional knowledge graph includes one or more additional nodes and edges, not found in the general-purpose knowledge graph, that convey a relationship between one or more of the identified entities and the developing event; and
subsequent to the constructing, querying the event-specific provisional knowledge graph for new information about the newly-detected developing event; and
causing one or more computing devices to render, as output, the new information.