Providing a visual and conversational experience in support of recommendations
First Claim
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1. A method, comprising:
- receiving, by a processor implemented recommender manager, a query identifying a source entity, the source entity being of a first entity-type;
generating, by the recommender manager, a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity;
computing, by the recommender manager, feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type;
computing, by the recommender manager, an aggregated score for each candidate entity by combining all of the feature values for each candidate entity;
generating, by the recommender manager, a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and
identifying, by the recommender manager, entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph.
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Abstract
The mapping system and method comprises receiving a query identifying a source entity, the source entity being of a first entity-type; generating a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; and computing feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type.
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Citations
20 Claims
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1. A method, comprising:
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receiving, by a processor implemented recommender manager, a query identifying a source entity, the source entity being of a first entity-type; generating, by the recommender manager, a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; computing, by the recommender manager, feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type; computing, by the recommender manager, an aggregated score for each candidate entity by combining all of the feature values for each candidate entity; generating, by the recommender manager, a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and identifying, by the recommender manager, entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause:
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receiving, by a processor, a query identifying a source entity, the source entity being of a first entity-type; generating, by the processor, a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; computing, by the processor, feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type; computing, by the processor, an aggregated score for each candidate entity by combining all of the feature values for each candidate entity; generating, by the processor, a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and identifying, by the processor, entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph. - View Dependent Claims (12, 13, 14, 15)
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16. A system, comprising a processor and a non-transitory memory, the system configured to:
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receive a query identifying a source entity, wherein the source entity is a first entity-type; generate a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; compute feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type; compute an aggregated score for each candidate entity by combining all of the feature values for each candidate entity; generate a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and identify entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph. - View Dependent Claims (17, 18, 19, 20)
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Specification