RANKING RELEVANT ATTRIBUTES OF ENTITY IN STRUCTURED KNOWLEDGE BASE
First Claim
1. A system, comprising:
- at least one knowledge base of entities, entity types, and entity attributes;
a features component that computes intermediate features of the entities and attributes, and aggregates the intermediate features to output a final feature set of features for each entity-attribute tuple;
a relevance component that generates a relevance score for a given entity and associated attributes based on the feature set;
a ranking component that ranks the attributes of the given entity based on the relevance scores; and
a microprocessor that executes computer-executable instructions associated with at least one of the features component, relevance component, or the ranking component.
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Abstract
Architecture that addresses at least the problem of ranking the relevant attributes for a given entity within the context of a structured knowledge base (SKB). The architecture utilizes the attribute, entity type statistics, and the taxonomy of the attributes to consistently and efficiently rank attributes for each and every type of entity in the SKB. Using the SKB, intermediate features are computed, including the importance or popularity each entity type for every entity, inverse document frequency (IDF) computation for each attribute on a global basis, IDF computation for entity types, and the popularity of attributes for each entity type. The intermediate features are aggregated to obtain a final feature set, which can be used in combination with human judgments to train a machine learned classifier model to produce and predict a relevance score for a given entity and each of its attributes. The attributes are ranked for each entity using this score.
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Citations
20 Claims
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1. A system, comprising:
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at least one knowledge base of entities, entity types, and entity attributes; a features component that computes intermediate features of the entities and attributes, and aggregates the intermediate features to output a final feature set of features for each entity-attribute tuple; a relevance component that generates a relevance score for a given entity and associated attributes based on the feature set; a ranking component that ranks the attributes of the given entity based on the relevance scores; and a microprocessor that executes computer-executable instructions associated with at least one of the features component, relevance component, or the ranking component. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method performed by a computer system executing machine-readable instructions, the method comprising acts of:
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receiving one or more structured knowledge bases of entities and attributes; computing intermediate features of the entities and attributes; aggregating the intermediate features to output a final feature set of features for each entity-attribute tuple; generating a relevance score for a given entity and each of its associated attributes based on the feature set; ranking the attributes of the given entity based on the relevance scores; and configuring a microprocessor to execute instructions in a memory associated with at least one of the acts of computing, aggregating, generating, or ranking. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A method performed by a computer system executing machine-readable instructions, the method comprising acts of:
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receiving a structured knowledge base of entities and attributes; computing intermediate features of the entities and attributes, the intermediate features include importance of each entity type for each entity, popularity of attributes for each entity type, term frequency compensation for each attribute on a global basis, and term frequency compensation for each entity type; aggregating the intermediate features to output a final feature set of features; training a classifier model using the final feature set of features; generating a relevance score for a given entity and associated attributes based on the classifier model; ranking the attributes of the given entity based on the relevance scores; and configuring a microprocessor to execute instructions in a memory associated with at least one of the acts of computing, aggregating, training, generating, or ranking. - View Dependent Claims (19, 20)
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Specification