Abstract: A data localization service is provided for a web browser residing on a computing device. Depending upon the availability of the network connection as well as the level of native support in the browser, the data localization service will support different levels of service/performance to optimize the user experience. To do so, the data localization service includes a priority handler configured to receive a request to localize data from a requesting client application and provide in response thereto a localized representation of the data to the requesting client application. The data localization service may also include a native data localizer configured to receive a request to localize data from the priority handler and localize the data in accordance with a localization preference parameter indicative of a locale. The native data localizer may be a function integrated into the script interpreter of the web browser.

Abstract: The disclosed subject matter provides a system, computer readable storage medium, and a method providing an audio and textual transcript of a communication. A conferencing services may receive audio or audio visual signals from a plurality of different devices that receive voice communications from participants in a communication, such as a chat or teleconference. The audio signals representing voice (speech) communications input into respective different devices by the participants. A translation services server may receive over a separate communication channel the audio signals for translation into a second language. As managed by the translation services server, the audio signals may be converted into textual data. The textual data may be translated into text of different languages based the language preferences of the end user devices in the teleconference. The translated text may be further translated into audio signals.

Abstract: A computer-implemented method for generating a machine-learning model can include receiving, at a computing device having one or more processors, a plurality of reported phone numbers from telephone users, a plurality of posted phone numbers from one or more websites, and transcriptions of messages associated with a plurality of calling phone numbers. The machine-learning model is generated based on these various inputs and stored at the computing device. The model is configured to determine a probability that an unknown phone message is unwanted based on a phone number from which the unknown phone message originated.

Abstract: Information about named entities referenced in an electronic book (ebook) is provided to a client device. An ebook identifier identifying the ebook is received from the client device. A set of layers available for use with the ebook is determined. The layers in the set provide information associated with the ebook and a layer in the set provides information associated with named entities referenced in content of the ebook. A content range identifying a range of content of the ebook for which layer information is requested and an identification of one or more of the layers in the set for which layer information is requested is received from the client device. Layer information associated with the ebook content identified by the content range for the identified layers is transmitted to the client device. The transmitted layer information includes information associated with named entities referenced by ebook content.

Abstract: Methods and systems for constructing a taxonomy based on hierarchical clustering are provided. The taxonomy is generated by first constructing a hierarchy of clusters using a clustering algorithm. A first level of the hierarchy of clusters is generated by providing a plurality of content files to a clustering algorithm. Subsequent levels of the hierarchy are generated by providing the clusters of the preceding levels to the clustering algorithm. Labels that characterize each cluster within the hierarchy are assigned to corresponding clusters. Labels and clusters are combined to form the taxonomy.

Abstract: The disclosed subject matter provides a system, computer readable storage medium, and a method providing an audio and textual transcript of a communication. A conferencing services may receive audio or audio visual signals from a plurality of different devices that receive voice communications from participants in a communication, such as a chat or teleconference. The audio signals representing voice (speech) communications input into respective different devices by the participants. A translation services server may receive over a separate communication channel the audio signals for translation into a second language. As managed by the translation services server, the audio signals may be converted into textual data. The textual data may be translated into text of different languages based the language preferences of the end user devices in the teleconference. The translated text may be further translated into audio signals.

Abstract: A method and system of classifying documents is provided. The method includes receiving a stream of documents from at least one user wherein each document includes a topic of information relating to a customer support issue or sentiment. The method includes classifying each of the received documents using a plurality of trained classifiers, the classification based on a voting by the trained classifiers, each document labeled according to a similar topic. A drift of the topic of one or more of the classifications is determined wherein the drift is related to the received documents that include information relating to an unclassified customer support issue or sentiment. If the determined drift exceeds a predetermined threshold range, rebuilding the plurality of classifiers to include a second set of classifiers trained to recognize the unclassified customer support issue or sentiment.

Abstract: Techniques for determining one or more preferred languages for a user are provided. The preferred languages may be determined based upon a set of language indicators. The language indicators are analyzed using, for example, rules-based techniques, clustering, language classifiers, and the like, or combinations thereof. Language indicators can include or be derived from information about the user's behavior, location, preferences, social connections, or other data related to the user.

Abstract: Information about named entities referenced in an electronic book (ebook) is provided to a client device. An ebook identifier identifying the ebook is received from the client device. A set of layers available for use with the ebook is determined. The layers in the set provide information associated with the ebook and a layer in the set provides information associated with named entities referenced in content of the ebook. A content range identifying a range of content of the ebook for which layer information is requested and an identification of one or more of the layers in the set for which layer information is requested is received from the client device. Layer information associated with the ebook content identified by the content range for the identified layers is transmitted to the client device. The transmitted layer information includes information associated with named entities referenced by ebook content.

Abstract: A computer-implemented method can include receiving an input via a first keyboard associated with a first language. The method can include determining a first character string based on the input and the first keyboard. The method can include determining a first probability score indicative of a likelihood that the first character string is appropriate in the first language. The method can include determining a second character string based on the input and a second keyboard associated with a second language when the first probability score is less than a first threshold. The method can include determining a second probability score indicative of a likelihood that the second character string is appropriate in the second language. Based on the probability scores, the method can also include generating an output including at least one of the first and character strings.

Abstract: Techniques for determining one or more preferred languages for a user are provided. The preferred languages may be determined based upon a set of language indicators. The language indicators are analyzed using, for example, rules-based techniques, clustering, language classifiers, and the like, or combinations thereof. Language indicators can include or be derived from information about the user's behavior, location, preferences, social connections, or other data related to the user.

Abstract: A set of language tags in a backend application can be passed to a frontend application in the form of a language selection tool. The disclosure creates a mapping between the frontend and backend application of at least one non-default language descriptor string onto a language tag of the backend application. The frontend language selection tool then displays to the user the non-default language descriptor string. The use of non-default language descriptor strings clarifies to the user otherwise ambiguous language identifiers.

Abstract: Techniques for determining one or more preferred languages for a user are provided. The preferred languages may be determined based upon a set of language indicators. The language indicators are analyzed using, for example, rules-based techniques, clustering, language classifiers, and the like, or combinations thereof. Language indicators can include or be derived from information about the user's behavior, location, preferences, social connections, or other data related to the user.

Abstract: The disclosed subject matter provides a system, computer readable storage medium, and a method providing an audio and textual transcript of a communication. A conferencing services may receive audio or audio visual signals from a plurality of different devices that receive voice communications from participants in a communication, such as a chat or teleconference. The audio signals representing voice (speech) communications input into respective different devices by the participants. A translation services server may receive over a separate communication channel the audio signals for translation into a second language. As managed by the translation services server, the audio signals may be converted into textual data. The textual data may be translated into text of different languages based the language preferences of the end user devices in the teleconference. The translated text may be further translated into audio signals.

Abstract: A data localization service is provided for a web browser residing on a computing device. Depending upon the availability of the network connection as well as the level of native support in the browser, the data localization service will support different levels of service/performance to optimize the user experience. To do so, the data localization service includes a priority handler configured to receive a request to localize data from a requesting client application and provide in response thereto a localized representation of the data to the requesting client application. The data localization service may also include a native data localizer configured to receive a request to localize data from the priority handler and localize the data in accordance with a localization preference parameter indicative of a locale. The native data localizer may be a function integrated into the script interpreter of the web browser.

Abstract: Methods, systems, and computer programs are presented for creating recommendations to add enhanced content to a post being created in a social network. One method includes an operation for detecting, using one or more computing devices, user input for a social post before the social post is submitted on the social network. The user input is analyzed, using the one or more computing devices, as is being entered to determine relevant content. Further, the method includes another operation for providing for display, using the one or more computing devices, the content recommendations, with the option to select one or more items on the content. If any of the recommendations are selected, the social post is provided for display, using the one or more computing devices, with the user input and with the selected recommendations.

Abstract: Methods and systems for use in labeling documents within a cluster are provided. One example method includes assembling a set of documents including a first plurality of previously clustered documents and a second plurality of documents. Each of the first plurality of previously clustered documents has at least one label identifying a topic to which content of the document relates. The method includes partitioning documents from the set of documents into multiple clusters, determining if a dominant topic exists within one of the multiple clusters, determining a metric value for one of the multiple clusters based on the number of documents within the one of the multiple clusters having a label identifying the determined dominant topic, and labeling at least documents from the second plurality of documents within the one of the multiple clusters with the label identifying the dominant topic when the metric value exceeds a predetermined threshold.

Abstract: Computer implemented techniques for performing transliteration of input text in a first character set to a second character set are disclosed. The techniques include receiving input text and determining a set of possible transliterations of the input text based on a plurality of mapping standards. Each mapping standard defines a mapping of characters in the first character set to characters in the second character set. The techniques further include determining a set of candidate words in the target language based on the possible transliterations and a text corpus. The techniques also include determining a likelihood score for each one of the candidate words based on a language model in the target language previously received words. The techniques also include providing one or more candidate words based on the likelihood scores and receiving a user selection indicating one of the candidate words.

Abstract: A method and system of classifying documents is provided. The method includes receiving a plurality of documents from at least one user, wherein each document includes information relating to a customer support issue or sentiment and identifying at least one customer support issue or sentiment contained within each document. The method also includes classifying the documents satisfying a confidence threshold using a classifier, clustering the remainder of the plurality of documents into groups using a clustering engine, the clustering engine applying a word analysis, and outputting a frequency of each identified customer support issue or sentiment, the frequency based on the classifying or the clustering.

Abstract: A computer-implemented method executes instructions stored on a computer-readable medium. The method includes accessing a hierarchy of clusters, wherein each cluster includes at least one content file, and a label is associated with each cluster. The method further includes calculating a topic purity score for each cluster, and selecting a first cluster and a second cluster from the hierarchy of clusters, wherein the topic purity score of the first cluster and the second cluster are less than a purity threshold. The method also includes creating a third cluster by combining the content files included within the first cluster and the second cluster, determining a parent category of the first cluster and the second cluster, wherein the parent category is at a level within the hierarchy higher than a level of the first cluster and the second cluster, and associating a label of the parent category with the third cluster.