Abstract: Techniques for context-based queryless presentation of items are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the triggering event. One or more results items identifying the one or more matching items are caused to display. Result items may be displayed in association with an explanation that identifies context values used to select an item or one or more attributes of the item that are relevant to a user or the inferred query.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, n-grams from the text of the communication; identifying mention-terms from the extracted n-grams, each mention-term being a noun-phrase; calculating a term-score for each mention-term based on a frequency of occurrence of the mention-term in the communications; and generating a mentions-module including mentions, each mention including a mention-term having a term-score greater than a threshold term-score and text from communications comprising the mention-term.

Abstract: In one embodiment, a method includes receiving, from a link-search interface of a client device, a search query from a first user of an online social network. The link-search interface is associated with a composer interface in which the first user is composing a first post. The method further includes searching a web index of an online social network to identify one or more external objects matching a search query. The web index identifies a plurality of external objects hosted by third-party systems that have been posted to the online social network, and each search result comprises a reference to the respective external object and a link to the external object. The method further includes embedding, in the first post, a link to a first external object referenced by a first search result selected by the first user.

Abstract: In one embodiment, a method includes receiving, from a client system of a first user, a request associated with a particular content item; identifying communications authored by one or more users, each identified communication being associated with the particular content item; generating one or more search-results modules related to the particular content item, each search-results module being of a particular module type, wherein each search-results module includes information from a subset of the identified communications, the information corresponding to the particular module type of the search-results module, and wherein a number of communications in the subset of the identified communications including each search-results module is greater than a module-specific threshold number of communications; and sending, to the client system, a search-results interface comprising one or more of the search-results modules.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; calculating, for each of the communications, sentiment-scores corresponding to sentiments, wherein each sentiment-score is based on a degree to which n-grams of the text of the communication match sentiment-words associated with the sentiments; determining, for each of the communications, an overall sentiment for the communication based on the calculated sentiment-scores for the communication; calculating sentiment levels for the particular content item corresponding sentiments, each sentiment level being based on a total number of communications determined to have the overall sentiment of the sentiment level; and generating a sentiments-module including sentiment-representations corresponding to overall sentiments having sentiment levels greater than a threshold sentiment level.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, quotations from the text of the communication; determining, for each extracted quotation, partitions of the quotation; grouping the extracted quotations into clusters based on a respective degree of similarity among their respective partitions; calculating a cluster-score for each cluster based on a frequency of occurrence of partitions of quotations in the cluster in the communications; and generating a quotations-module comprising representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score.

Abstract: Techniques for context-based queryless presentation of items are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the triggering event. One or more results items identifying the one or more matching items are caused to display. Result items may be displayed in association with an explanation that identifies context values used to select an item or one or more attributes of the item that are relevant to a user or the inferred query.

Abstract: Techniques for context-based queryless presentation of items are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the triggering event. One or more results items identifying the one or more matching items are caused to display. Result items may be displayed in association with an explanation that identifies context values used to select an item or one or more attributes of the item that are relevant to a user or the inferred query.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, quotations from the text of the communication; determining, for each extracted quotation, partitions of the quotation; grouping the extracted quotations into clusters based on a respective degree of similarity among their respective partitions; calculating a cluster-score for each cluster based on a frequency of occurrence of partitions of quotations in the cluster in the communications; and generating a quotations-module comprising representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, n-grams from the text of the communication; identifying mention-terms from the extracted n-grams, each mention-term being a noun-phrase; calculating a term-score for each mention-term based on a frequency of occurrence of the mention-term in the communications; and generating a mentions-module including mentions, each mention including a mention-term having a term-score greater than a threshold term-score and text from communications comprising the mention-term.

Abstract: In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; calculating, for each of the communications, sentiment-scores corresponding to sentiments, wherein each sentiment-score is based on a degree to which n-grams of the text of the communication match sentiment-words associated with the sentiments; determining, for each of the communications, an overall sentiment for the communication based on the calculated sentiment-scores for the communication; calculating sentiment levels for the particular content item corresponding sentiments, each sentiment level being based on a total number of communications determined to have the overall sentiment of the sentiment level; and generating a sentiments-module including sentiment-representations corresponding to overall sentiments having sentiment levels greater than a threshold sentiment level.

Abstract: In one embodiment, a method includes receiving, from a client system of a first user, a request associated with a particular content item; identifying communications authored by one or more users, each identified communication being associated with the particular content item; generating one or more search-results modules related to the particular content item, each search-results module being of a particular module type, wherein each search-results module includes information from a subset of the identified communications, the information corresponding to the particular module type of the search-results module, and wherein a number of communications in the subset of the identified communications including each search-results module is greater than a module-specific threshold number of communications; and sending, to the client system, a search-results interface comprising one or more of the search-results modules.

Abstract: In one embodiment, a method includes receiving, from a link-search interface of a client device, a search query from a first user of an online social network. The link-search interface is associated with a composer interface in which the first user is composing a first post. The method further includes searching a web index of an online social network to identify one or more external objects matching a search query. The web index identifies a plurality of external objects hosted by third-party systems that have been posted to the online social network, and each search result comprises a reference to the respective external object and a link to the external object. The method further includes embedding, in the first post, a link to a first external object referenced by a first search result selected by the first user.

Abstract: In one embodiment, a method includes receiving a search query. The method includes generating query commands based on the search query. The of query commands include a first query command comprising a query constraint for objects having a first privacy setting, and a second query command comprising a query constraint for objects having a second privacy setting, wherein the second privacy setting is more restrictive than the first privacy setting. The method includes searching to identify a first set of objects that match the first query command, and a second set of objects associated that match the second query command. The method includes generating one or more search results and sending a search-results page to the client system of the first user for display.

Abstract: Techniques for context-based queryless presentation of items are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the triggering event. One or more results items identifying the one or more matching items are caused to display. Result items may be displayed in association with an explanation that identifies context values used to select an item or one or more attributes of the item that are relevant to a user or the inferred query.

Abstract: Techniques for context-based queryless presentation of recommendations are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a recommendation triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the recommendation triggering event. One or more results items identifying the one or more matching items are caused to display. A result items may be displayed in association with an explanation that identifies context values used to select an item for recommendation or one or more attributes of the item that are relevant to a user or the inferred query.

Abstract: A recommendation engine provides a plurality of users with a recommendation for a common group action. The recommendation engine can take into user information such as explicit or implicit preferences of the participant of the group action in recommending a group action, such as shopping together, buying together, going to an event together, engaging in an activity together, etc. By considering the group, as well as the individuals, the recommendation engine can make recommendations optimized for a goal of one or more of the individuals, or for a group goal, which might not have been a recommendation made for any one of the individuals if considered in isolation. Additionally, in certain embodiments, the recommendation engine recommends an item related to a planned group activity for a group including a plurality of individuals based on information relating to each of the plurality of individuals.

Abstract: Techniques for context-based queryless presentation of recommendations are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a recommendation triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the recommendation triggering event. One or more results items identifying the one or more matching items are caused to display. A result items may be displayed in association with an explanation that identifies context values used to select an item for recommendation or one or more attributes of the item that are relevant to a user or the inferred query.