Abstract: Methods and apparatus related to associating a task with a user based on the user selecting a task suggestion that is provided to the user in response to a user query. In some implementations, the task may be identified based on similarities between the words and/or phrases of the user query and a task suggestion that is associated with a task. In some implementations, the task may be identified based on user data associated with the user. In some implementations, the task may be associated with additional information related to completing the task.

Abstract: A system and method for generating a stream of content with candidate content items associated with a likelihood of being interesting to a user. A model generation engine generates a model for a user. A scoring engine obtains candidate content items and compares candidate content items to a model to determine the most interesting content items. A user interface engine organizing first and second content items in a first direction and a third content item in a second direction. The user interface engine receives feedback that includes a request for additional content items or a request to remove an interest associated with a selected content item from the model. The model generation engine updates the model in response to feedback.

Abstract: Methods and apparatus related to associating a task with a user based on the user selecting a task suggestion that is provided to the user in response to a user query. In some implementations, the task may be identified based on similarities between the words and/or phrases of the user query and a task suggestion that is associated with a task. In some implementations, the task may be identified based on user data associated with the user. In some implementations, the task may be associated with additional information related to completing the task.

Abstract: Methods and apparatus related to determining an association between a message trail and a task entry of a user and associating an n-gram with the task entry, wherein the n-gram is based on one or more messages of the message trail. A similarity score between the n-gram and one or more aspects of the associated task entry may be determined. The similarity score may be utilized, for example, to determine when to associate the n-gram with the task entry and/or how to utilize the associated n-gram with the task entry.

Abstract: A system and method for generating a real-time stream of content from heterogeneous data sources and a real-time index. The heterogeneous data sources include search, entertainment, social activity and activity on third-party sites. A fetching unit retrieves recent content that is indexed in the real-time index according to keywords. A model generation engine generates a model based on user activities. The mixer compares candidate content items from the heterogeneous data sources and the real-time index to the model to generate scores for each item and generates a stream of content based on the scores.

Abstract: Methods and apparatus related to determining one or more user habits for a user. A group of one or more past user activity occurrences of a user may be determined based on similarity between the past user activity occurrences of the group. A user habit may be determined based on the past user activity occurrences of the group.

Abstract: The disclosure includes a system and method for providing a customized stream of content to a user. The system includes: an item sourcer for gathering one or more content items from one or more content sources; a behavior indicator module and scorer for determining one or more behavior scores for the one or more content items; a content indicator module and scorer for determining one or more content scores for the one or more content items; a score combiner for aggregating the one or more behavior scores and the one or more content scores to generate one or more item scores for the one or more content items; a content diversifier for determining one or more diverse items from the one or more content items; and a stream generator for generating a customized stream of content for the user from the one or more diverse items.

Abstract: Methods and apparatus related to associating an event attribute with a user based on a group of electronic messages associated with the user. An event may be associated with the group of electronic messages. One or more event attributes of the event may be determined, including an event location identifier that identifies a physical event location. One or more of the event attributes may be determined based on the group of electronic messages. Location data of the user may be identified and a likelihood that the user interacted with the physical event location may be determined based on comparing the location data of the user to the event location identifier. The likelihood that the user interacted with the physical event location and at least one of the event attributes determined based on the group of electronic messages may be associated with the user.

Abstract: Methods and apparatus related to determining an activity of a user based on sensor readings from sensor(s), and providing, for presentation to the user via a user interface output of a computing device of the user, information that is based on the determined activity. In some implementations, the information may be provided in response to input entered by the user via a user interface input device of the computing device of the user. In some implementations, the input may be a search query and the information may be search results. In some implementations, the input may be a partial query and the information may be query suggestions.

Abstract: A system and method for generating a channel includes a channel engine that retrieves candidate content items based on a topic from heterogeneous data sources. The channel engine generates a stream of content with selected content items and populates the stream of content for the channel and providing the stream of content to users associated with the channel. In response to receiving feedback, the channel engine modifies the at least one topic based at least in part on the feedback. The scoring engine generates a second stream of content from the first stream of content that is personalized for the first user based at least in part on a model. Other users can subscribe to the second stream.

Abstract: Methods, systems, and apparatus for allocating an offer based, in part, on a user's utility. In one aspect, a method includes receiving, at a data processing apparatus, data describing a purchase intent for a set of items, the purchase intent being for a user; receiving, at the data processing apparatus, from each offeror in a set of offerors: a corresponding offer from the offeror, each offer applying to one or more items in the set of items, and a corresponding valuation of the offer by the offeror for presentation of the offer to the user; for each offer in the set of offers, determining, by the data processing apparatus, a corresponding utility to the user based on a user utility model, and adjusting the valuation for the offer based on the corresponding utility determined for the offer to generate an adjusted valuation for the offer.

Abstract: A system and method for generating a stream of content for a channel. The channel application includes a content categorizer, a scoring engine and a channel engine. The content categorizer categorizes new content items received from heterogeneous data sources. The channel engine identifies a channel category for a user based at least in part on at least one of a historical trend and a user activity. The scoring engine queries the new content items based on the channel category and at least one other channel attribute. The scoring engine retrieves candidate content items that include the channel category and the other channel attribute. The scoring engine then generates a stream of content from the candidate content items for the channel.

Abstract: Methods and apparatus related to determining an association between a message trail and a task entry of a user and associating an n-gram with the task entry, wherein the n-gram is based on one or more messages of the message trail. A similarity score between the n-gram and one or more aspects of the associated task entry may be determined. The similarity score may be utilized, for example, to determine when to associate the n-gram with the task entry and/or how to utilize the associated n-gram with the task entry.

Abstract: Methods and apparatus related to determining a likelihood that a task is completed. One or more task completion entities with which the user can interact to complete the task may be determined. One or more activity data indicators may be determined for a given entity of the task completion entities. The activity data indictors are indicative of the user performing the action through interaction with the given entity. User activity data may be received and compared with the activity data indicators to determine one or more matching activity data indicators of the activity data indicators that match the user activity data. A likelihood that the task is completed may be determined based on the matching activity data indicators.

Abstract: Methods and apparatus related to identifying one or more messages sent by a user, identifying two or more contacts that are associated with one or more of the messages, determining a strength of relationship score between identified contacts, and utilizing the strength of relationship scores to provide additional information related to the contacts. A strength of relationship score between a contact and one or more other contacts may be determined based on one or more properties of one or more of the messages. In some implementations, contacts groups may be determined based on the strength of relationship scores. In some implementations, contacts groups may be utilized to disambiguate references to contacts in messages. In some implementations, contacts group may be utilized to provide suggestions to the user of additional contacts of a contacts group that includes the indicated recipient contact of a message.

Abstract: Methods and apparatus related to providing additional information related to a vague term in a message. For example, in some implementations, one or more messages sent by a sender and received by one or more recipients may be identified, a vague term in the message may be identified, a user-restricted database may be identified that is associated with the sender or a recipient, and additional information related to the vague term may be determined from the user-restricted database. A vague term is a term which may have multiple meanings and that can be clarified with additional information. In some implementations, user-restricted databases may include additional information that is associated with the user that may be utilized to replace the vague term with a clarified term. In some implementations, a user-restricted database may be utilized to identify additional information in another database that may be utilized to clarify the vague term.

Abstract: Methods and apparatus related to determining an association between a message trail and a task entry of a user and associating an n-gram with the task entry, wherein the n-gram is based on one or more messages of the message trail. A similarity score between the n-gram and one or more aspects of the associated task entry may be determined. The similarity score may be utilized, for example, to determine when to associate the n-gram with the task entry and/or how to utilize the associated n-gram with the task entry.

Abstract: Methods and apparatus related to identifying one or more messages sent by a user, identifying two or more contacts that are associated with one or more of the messages, determining a strength of relationship score between identified contacts, and utilizing the strength of relationship scores to provide additional information related to the contacts. A strength of relationship score between a contact and one or more other contacts may be determined based on one or more properties of one or more of the messages. In some implementations, contacts groups may be determined based on the strength of relationship scores. In some implementations, contacts groups may be utilized to disambiguate references to contacts in messages. In some implementations, contacts group may be utilized to provide suggestions to the user of additional contacts of a contacts group that includes the indicated recipient contact of a message.

Abstract: Methods and apparatus related to adjusting the ranking of a suggestion for a geographic location based on determining how many of one or more users visited the geographic location after receiving the suggestion. In some implementations the one or more users may belong to first grouping of users and the ranking may be adjusted only for suggestions to the first grouping of users. In some implementations it may be determined if a second grouping of users visited the geographic location after receiving the suggestion. In some implementations a property of the given geographic location may be determined based on a comparison of how many of the second grouping of users visited the given geographic location after receiving the suggestion and how many of the one or more users visited the given geographic location after receiving the suggestion.

Abstract: Methods and apparatus related to associating a quality measure with a given location. For example, an anticipated distance value for a given location may be identified that is indicative of anticipated time and/or distance to reach the given location. At least one actual distance may be identified that is indicative of actual time for the one or more members to reach the given location. In some implementations, the anticipated/actual distance values may include one or more distributions. A quality measure is then determined based on a comparison of the anticipated distance value and the identified actual distance value. The quality measure is associated with the given location. The quality measure may be further based on additional factors.