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:
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 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 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 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.
Abstract:
Methods and apparatus related to associating a task completion step with one or more tasks. A task group is determined based on similarity between the tasks of the task group, a task completion step of one of the tasks of the task group is identified, and one or more of the other tasks of the task group are associated with the task completion step. In some implementations, the task group is determined based on similarity between entities that are associated with the tasks of the task group. In some implementations, the task group is determined based on textual representations that are associated with the tasks of the task group.
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 identifying a plurality of user locations, determining an activity of the user based on the identified user locations, and providing information to the user based on the determined activity of the user. In some implementations, the information may be a user activity suggestion for a user to perform. In some implementations, the information may be provided to the user in response to input from 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.