Abstract: Methods and apparatus are described herein for identifying tasks in messages. In various implementations, natural language processing may be performed on a received message to generate an annotated message. The annotated message may be analyzed pursuant to a grammar. A portion of the message may be classified as a user task entry based on the analysis of the annotated message.

Abstract: Methods, systems, and apparatus for obtaining a resource, identifying a first portion of text of the resource that is characterized as a question, and a second part of text of the resource that is characterized as an answer to the question, identifying an entity that is referenced by one or more terms of the text that is characterized as the question, a relationship type that is referenced by one or more other terms of the text that is characterized as the question, and an entity that is referenced by the text that is characterized as the answer to the question, and adjusting a score for a relationship of the relationship type for the entity that is referenced by the one or more terms of the text that is characterized as the question and the entity that is referenced by the text that is characterized as the answer to the question.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying documents. One of the methods includes obtaining a collection of training documents, the training documents including positive documents identified as being longform documents and negative documents identified as not being longform documents; extracting one or more features from the training documents, wherein the features represent lexical or textual content of the training documents; and generating a longform document classifier trained using feature instances extracted from the training documents, wherein the generated longform document classifier is trained such that input documents are classified as being longform documents or classified as not being longform documents.

Abstract: Systems and methods are disclosed for using an additive context model for entity disambiguation. An example method may include receiving a span of text from a document and a phrase vector for the span. The phrase vector may have a quantity of features and represent a context for the span. The method also includes determining a quantity of candidate entities from a knowledge base that have been referred to by the span. For each of the quantity of candidate entities, the method may include determining a support score for the candidate entity for each feature in the phrase vector, combining the support scores additively, and computing a probability that the span resolves to the candidate entity given the context. The method may also include resolving the span to a candidate entity with a highest probability.

Abstract: Methods and apparatus are described herein for identifying tasks in messages. In various implementations, natural language processing may be performed on a received message to generate an annotated message. The annotated message may be analyzed pursuant to a grammar. A portion of the message may be classified as a user task entry based on the analysis of the annotated message.

Abstract: A computer-implemented technique can receive a plurality of photos and automatically select a subset of the plurality of photos having a high degree of representativeness by jointly maximizing both photo quality and photo diversity to obtain a photo album. The technique can determine one or more clusters for the photo album using a hierarchical clustering algorithm, and store the photo album according to the one or more clusters. The technique can control the manner in which the photo album is displayed using the one or more clusters. The technique can adjust at least one of the one or more clusters and the automatic photo album generation based on user input. The user input can include at least one of adding, deleting, and moving a photo with respect to the one or more clusters. The technique can then re-cluster, automatically generate a new photo album, and/or adjust the presentation.

Abstract: A computer-implemented technique can include obtaining a training corpus including pairs of (i) documents and (ii) corresponding abstracts. The technique can include identifying a set of entity mentions in each abstract and each corresponding document based on their respective part-of-speech (POS) tags and dependency parses. The technique can include clustering the sets of entity mentions referring to a same underlying entity to obtain clusters for each document and each corresponding abstract. The technique can include aligning specific abstract entity mentions to corresponding document entity mentions to obtain a set of aligned abstract and document entities. The technique can include labeling the set of aligned entities as salient and unaligned entities as non-salient to generate a labeled corpus. The technique can also include training features of a classifier using the labeled corpus to obtain a trained classifier.

Abstract: Methods and apparatus are described herein for identifying tasks in messages. In various implementations, natural language processing may be performed on a received message to generate an annotated message. The annotated message may be analyzed pursuant to a grammar. A portion of the message may be classified as a user task entry based on the analysis of the annotated message.

Abstract: Methods and apparatus related to associating a segment of an electronic message with one or more segment addressees. One or more message addressees of an electronic message may be identified, the one or more message addressees identifying at least one recipient of the electronic message. A segment of the electronic message may be identified via one or more processors. One or more segment addressees may be determined from the at least one recipient, the one or more segment addressees identifying an addressee for the identified segment. One or more aspects of the segment may be associated with the one or more segment addressees. An indication pertaining to the one or more aspects of the segment may be provided to the one or more segment addressees.

Abstract: Methods and apparatus related to determining coreference resolution using distributed word representations. Distributed word representations, indicative of syntactic and semantic features, may be identified for one or more noun phrases. For each of the one or more noun phrases, a referring feature representation and an antecedent feature representation may be determined, where the referring feature representation includes the distributed word representation, and the antecedent feature representation includes the distributed word representation augmented by one or more antecedent features. In some implementations the referring feature representation may be augmented by one or more referring features. Coreference embeddings of the referring and antecedent feature representations of the one or more noun phrases may be learned. Distance measures between two noun phrases may be determined based on the coreference embeddings.

Abstract: Methods and apparatus related to associating a segment of an electronic message with one or more segment addressees. One or more message addressees of an electronic message may be identified, the one or more message addressees identifying at least one recipient of the electronic message. A segment of the electronic message may be identified via one or more processors. One or more segment addressees may be determined from the at least one recipient, the one or more segment addressees identifying an addressee for the identified segment. One or more aspects of the segment may be associated with the one or more segment addressees. An indication pertaining to the one or more aspects of the segment may be provided to the one or more segment addressees.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing app store search results. An example method includes responsive to a first search query directed to an app store: revising the first search query to produce a second search query different from the first search query; obtaining, from an Internet search engine, second search results responsive to the second search query; analyzing the second search results to identify apps available on the app store that are relevant to the second search query; obtaining, from the app store, first search results responsive to the first search query that identify apps available in the app store; and modifying the first search results based on analyzing the second search results.

Abstract: Methods, systems, and apparatus for obtaining a resource, identifying a first portion of text of the resource that is characterized as a question, and a second part of text of the resource that is characterized as an answer to the question, identifying an entity that is referenced by one or more terms of the text that is characterized as the question, a relationship type that is referenced by one or more other terms of the text that is characterized as the question, and an entity that is referenced by the text that is characterized as the answer to the question, and adjusting a score for a relationship of the relationship type for the entity that is referenced by the one or more terms of the text that is characterized as the question and the entity that is referenced by the text that is characterized as the answer to the question.

Abstract: Methods and apparatus related to determining and scoring task indications. For example, methods and apparatus may determine a plurality of interrogative sentences in a plurality of messages, determine starting n-grams of the interrogative sentences, determine task indications based on the starting n-grams, and determine task association scores for the task indications. Each task indication may be determined based on a set of one or more starting n-grams that share similarities. One or more individuals and/or applications may assign one or more task association measures to a task indication based on likelihood that the task indication is associated with a task request. The task association score for the task indication may be determined based on the task association measures that are assigned to the task indication.

Abstract: A method for annotating a message executes at a computing device having one or more processors and memory. The memory stores one or more programs configured for execution by the one or more processors. A plurality of messages for a user is analyzed to determine whether a task reminder is derivable for any of the messages. In this way, task reminders are derived for at least a subset of the messages. A user interface for an electronic messaging application is provided. The interface includes a list of objects, one or more of which represents a collapsed state of a message in the message subset and comprises a summary, task reminder, and a dismissal affordance. Responsive dismissal affordance selection, the task reminder and the dismissal affordances are removed from the object.

Abstract: Implementations include systems and methods generate data for training or evaluating semantic analysis engines. For example, a method may include receiving documents from a corpus that includes an authoritative set of documents from an authoritative source. Each document in the authoritative set may be associated with an entity. A second set of documents from the corpus that do not overlap with the first set may include at least one link to a document in the authoritative set, the at least one link being associated with anchor text. For each document in the second set, the method may include identifying entity mentions in the document based on the anchor text. The method may include associating the entity mention with the entity in a graph-structured knowledge base or associating entity types with the entity mention. The method may also include training a semantic analysis engine using the identified entity mentions and associations.

Abstract: Methods and apparatus related to associating a segment of an electronic message with one or more segment addressees. One or more message addressees of an electronic message may be identified, the one or more message addressees identifying at least one recipient of the electronic message. A segment of the electronic message may be identified via one or more processors. One or more segment addressees may be determined from the at least one recipient, the one or more segment addressees identifying an addressee for the identified segment. One or more aspects of the segment may be associated with the one or more segment addressees. An indication pertaining to the one or more aspects of the segment may be provided to the one or more segment addressees.

Abstract: Methods and apparatus are described herein for identifying tasks in messages. In various implementations, natural language processing may be performed on a received message to generate an annotated message. The annotated message may be analyzed pursuant to a grammar. A portion of the message may be classified as a user task entry based on the analysis of the annotated message.

Abstract: A computer-implemented technique can receive, at a computing device including one or more processors, a plurality of photos. The technique can extract quality features and similarity features for each of the plurality of photos and can obtain weights for the various quality features and similarity features based on an analysis of a reference photo collection. The technique can generate a quality metric for each of the plurality of photos and can generate a similarity matrix for the plurality of photos by analyzing the various quality features and similarity features and using the obtained weights. The technique can perform joint global maximization of photo quality and photo diversity using the quality metrics and the similarity matrix in order to select a subset of the plurality of photos having a high degree of representativeness. The technique can then store the subset of the plurality of photos in a memory.

Abstract: A computer-implemented technique can receive a plurality of photos and automatically select a subset of the plurality of photos having a high degree of representativeness by jointly maximizing both photo quality and photo diversity to obtain a photo album. The technique can determine one or more clusters for the photo album using a hierarchical clustering algorithm, and store the photo album according to the one or more clusters. The technique can control the manner in which the photo album is displayed using the one or more clusters. The technique can adjust at least one of the one or more clusters and the automatic photo album generation based on user input. The user input can include at least one of adding, deleting, and moving a photo with respect to the one or more clusters. The technique can then re-cluster, automatically generate a new photo album, and/or adjust the presentation.