Abstract: Methods and apparatus related to receiving user task information indicative of an intended action of a user, determining additional information related to completion of the intended action, determining a completion step for the intended action based on the additional information, and providing the completion step to the user. The user task information may be received from a first source and the additional information may be determined from one or more additional sources that are distinct from the first source. Additional sources may include, for example, user data associated with the user and/or one or more non-user specific databases such as an entity database. Whether a completion step is provided to a user may be dependent on one or more factors such as, for example, the source of the user task information, the source of the additional information, and/or a trigger associated with the completion step.

Abstract: Methods and apparatus related to providing one or more completion step suggestions for a task that is associated with a user. In some implementations, the completion step suggestions may be provided to the user based on the satisfaction of a trigger condition. In some implementations, a trigger condition may be based on a user geographic location. In some implementations, a trigger condition may be based on an action of the user. In some implementations, a trigger condition may be based on a time when the associated task may be completed.

Abstract: Embodiments are directed towards providing word-by-word message completion for an incomplete response message, wherein the response message is composed in response to a received stimulus message. The message completion is based on a Response Completion Model (RCM) that may model both the language used in the incomplete response message and the contextual information in the received stimulus message. The RCM may be determined based on conversational stimulus-response data including stimulus-response message pairs. The RCM may be a mixture model and include a generic response language model based on an N-gram model, a Stimulus Model based on a Selection Model or a Topic. Model, and a mixture parameter. In some embodiments, at least one candidate next word for the incomplete response message is determined based on the RCM. The at least one candidate next word may be selected and included in the incomplete response message. A complete response message may be generated and provided to a user.

Abstract: Automatic generation of bid phrases for online advertising comprising storing a computer code representation of a landing page for use with a language model and a translation model (with a parallel corpus) to produce a set of candidate bid phrases that probabilistically correspond to the landing page, and/or to web search phrases. Operations include extracting a set of raw candidate bid phrases from a landing page, generating a set of translated candidate bid phrases using a parallel corpus in conjunction with the raw candidate bid phrases. In order to score and/or reduce the number of candidate bid phrases, a translation table is used to capture the probability that a bid phrase from the raw bid phrases is generated from a bid phrase from the set of translated candidate bid phrases. Scoring and ranking operations reduce the translated candidate bid phrases to just those most relevant to the landing page inputs.