Abstract: In one embodiment, a method includes receiving a text query from a client system of a user and parsing the text query to identify a primary entity referenced in the text query. The method also includes identifying one or more related entities for the primary entity based on one or more related-entity indexes associated with the primary entity and identifying one or more content objects matching the text query, each identified content object being associated with one or more of the related entities. The method also includes sending to the client system instructions for presenting one or more search results corresponding to one or more of the identified content objects, respectively, each search result including a reference to the associated related entity and a snippet for the related entity describing the relationship between the primary entity and the related entity.

Abstract: In one embodiment, a method includes receiving, from a client system associated with a first user of an online social network, a search query; parsing the search query to identify one or more n-grams; retrieving, for each identified n-gram, metadata from a mining-search-log database, where the metadata includes at least top N entity identifiers corresponding to entities associated with the identified n-gram and their respective click-through rates, and top K co-occurring n-grams for the identified n-gram; identifying a plurality of content objects matching the search query; ranking the content objects based on whether the content objects contain one or more of the top N entity identifiers or one or more of the top K co-occurring n-grams; and sending, to the client system, instructions for presenting one or more search results corresponding to the identified content objects in an order based on the ranking of the corresponding content objects.

Abstract: In one embodiment, a method includes by one or more computing machines: receiving a search query from a user, generating a normalized query based on the search query, identifying multiple objects matching the search query, and calculating an engagement score for each object. The engagement score is based on real-time counters and batch counters. Each counter includes: a key listing the object, normalized query, and one of multiple types of user interactions; and a value indicating a number of user interactions with the object performed in response to search queries normalizing to the normalized query. The value for real-time and batch counters indicates user interactions during first and second threshold windows of time, respectively. The method continues with sending, to the user, a search-results interface including results corresponding to the identified objects above a threshold engagement score, and updating the real-time counters based on user interactions with the search results.

Abstract: In one embodiment, a method includes receiving a text query from a client system of a user and parsing the text query to identify a primary entity referenced in the text query. The method also includes identifying one or more related entities for the primary entity based on one or more related-entity indexes associated with the primary entity and identifying one or more content objects matching the text query, each identified content object being associated with one or more of the related entities. The method also includes sending to the client system instructions for presenting one or more search results corresponding to one or more of the identified content objects, respectively, each search result including a reference to the associated related entity and a snippet for the related entity describing the relationship between the primary entity and the related entity.