Relevance in a knowledge graph
AssigneeApple Inc.
InventorsAkshay AGGARWAL, Fatih SUNOR, João Pedro LACERDA, Jeffrey A. POUND, Chiraag SUMANTH
Life of this patent
Estimating the term…
Abstract
Aspects of the subject technology provide a relevance prediction based on a database of entities and statistics of past interactions between the entities. A relevance of a target entity in the database given a context of entities in the database may be predicted by deriving a probability set of at least one conditional probability from the database for each of the context entities, and then applying a machine learning model to the probability set to produce the relevance of the target entity.
Claims20
A method, comprising:
- in response to a relevance query including a target entity and query context comprising one or more context entities:
- determining, from a database of entities including the target entity and the one or more context entities, a probability set for the target entity including one or more conditional probabilities for each of the one or more context entities, wherein the database includes statistics of interactions between pairs of entities in the relevance query;
- applying a machine learning model to the probability set to determine a relevance of the target entity for the query context;
- and
- taking an action based on the determined relevance.
A system, comprising:
- a processor;
- and
- a memory storing instructions, that when executed by the processor, cause the system to:
- in response to a relevance query including a target entity and query context comprising one or more context entities:
- determine, from a database of entities including the target entity and the one or more context entities, a probability set for the target entity including one or more conditional probabilities for each of the one or more context entities, wherein the database includes statistics of interactions between pairs of entities in the relevance query;
- apply a machine learning model to the probability set to determine a relevance of the target entity for the query context;
- and
- take an action based on the determined relevance.
A non-transitory computer readable memory storing instructions that, when executed by a processor, cause the processor to:
- in response to a relevance query including a target entity and query context comprising one or more context entities:
- determine, from a database of entities including the target entity and the one or more context entities, a probability set for the target entity including one or more conditional probabilities for each of the one or more context entities, wherein the database includes statistics of interactions between pairs of entities in the relevance query;
- apply a machine learning model to the probability set to determine a relevance of the target entity for the query context;
- and
- take an action based on the determined relevance.
Dependencies are inferred from the claim text.