Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: A technique for providing search results may include determining a first entity type, a second entity type, and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: A technique for providing search results may include determining a first entity type, a second entity type, and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: A technique for providing search results may include determining a first entity type, a second entity type, and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: A technique for providing search results may include determining a first entity type, a second entity type, and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: Implementations provide an enhanced search result to improve the user search experience. For example, the result may include insightful information relevant to the search query that was not specifically requested but that the user may find interesting, such as relationships shared between the two entities related to the query, a relationship between the two entities that does not commonly occur with another relationship shared by the entities, or strong secondary connections for an entity related to the query. In some implementations, insightful connections may also be unique facts for a particular entity. Unique facts may represent a superlative attribute of an entity such as, for example, the tallest actor, the oldest president, the most expensive stock, etc. Such shared relationships, rare relationships, and/or unique facts may be provided as part of the search results presented to the query requestor and may provide insight to the requestor about the entity.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: Methods, systems, and computer-readable media are provided for ranking search results. A search system may determine several metrics based on search results. The search system may determine weights for the metrics, wherein the weights are based in part on the type of entity included in the search. The search system may determine a score by combining the metrics and the weights. The search system may rank search results based on the score.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.

Abstract: Methods, systems, and computer-readable media are provided for ranking search results. A search system may determine several metrics based on search results. The search system may determine weights for the metrics, wherein the weights are based in part on the type of entity included in the search. The search system may determine a score by combining the metrics and the weights. The search system may rank search results based on the score.

Abstract: A technique for providing search results may include determining a first entity type, a second entity types and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: Implementations provide an enhanced search result to improve the user search experience. For example, the result may include insightful information relevant to the search query that was not specifically requested but that the user may find interesting, such as relationships shared between the two entities related to the query, a relationship between the two entities that does not commonly occur with another relationship shared by the entities, or strong secondary connections for an entity related to the query. In some implementations, insightful connections may also be unique facts for a particular entity. Unique facts may represent a superlative attribute of an entity such as, for example, the tallest actor, the oldest president, the most expensive stock, etc. Such shared relationships, rare relationships, and/or unique facts may be provided as part of the search results presented to the query requestor and may provide insight to the requestor about the entity.

Abstract: Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.