Abstract: A method and system is disclosed for evaluating a chat message sent between users of an online environment. The method may include receiving a chat message and parsing the message into words. The method determines the acceptability of the message by matching the message to a plurality of acceptable messages stored in a data structure. Upon determining the message does not match any acceptable messages, the method replaces each word in the message with grammatical metadata. The method may use templates to determine if the message has acceptable word combinations based on the metadata. The method may also compare the metadata to rules wherein the rules determine if the message has unacceptable word combinations based on the metadata. The method may send the message to a user upon determining words in the message do not match any word in a list of unacceptable words.

Abstract: A method is disclosed for evaluating a chat message sent between users of an online environment. The method may include associating each word in the chat message with metadata. The metadata identifies a word type and usage for each word in the chat message. This method may also include identifying one or more safety rules associated with the metadata. Each safety rule identifies an ordered sequence of one or more sets of words. This method may also include applying the safety rule to the chat message to determine whether a sequence of words in the chat message present in the ordered sequence of sets of words. Upon determining a word, from each set of words in the ordered sequence of sets of words, matches a respective one of the words in the chat message, the chat message is blocked from being sent to a message recipient.

Abstract: Methods, systems, and computer programs are presented for determining languages spoken by a user based on analysis of the information and activities of the user. One method includes an operation for extracting values for features, associated with a user of a social network, related to a language. Each feature is a primary or a secondary feature. For each primary feature, a determination is made whether the value of the feature exceeds a threshold. The method further includes operations for determining that the user speaks the language when at least one primary feature exceeds the respective threshold, and when no primary feature exceeds the respective threshold, analyzing values of the primary and secondary features to determine if the user speaks the language. The determination that the user speaks the language is stored in the user profile, and the user interface of the social network is customized based on the language.

Abstract: This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.

Abstract: Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.

Abstract: A method of ranking a set of candidate standardized titles selected from a corpus of standardized titles is disclosed. The set of candidate standardized titles are selected from the corpus of standardized titles as corresponding to a raw title. A combined inverse document frequency score is determined for each candidate standardized title in the set of candidate standardized titles. The combined inverse document frequency score is based on inverse frequency scores for each of a set of tokens derived from the set of candidate standardized titles. A ranking score is determined for each of the set of candidate standardized titles based on the combined inverse document frequency score. The ranking score for each of the set of candidate standardized titles is communicated for use by a separate module to improve an accuracy in a functionality of the separate module.

Abstract: Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.

Abstract: A method includes receiving an audio command by an electronic device to perform an action. Context related to the audio command is learned by one or more other electronic devices connected with the electronic device. One or more other actions are performed by the one or more other electronic devices based on learned context from the audio command received by the electronic device.

Abstract: This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.

Abstract: Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.

Abstract: Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.

Abstract: A method and system is disclosed for evaluating a chat message sent between users of an online environment. The method may include receiving a chat message and parsing the message into words. The method determines the acceptability of the message by matching the message to a plurality of acceptable messages stored in a data structure. Upon determining the message does not match any acceptable messages, the method replaces each word in the message with grammatical metadata. The method may use templates to determine if the message has acceptable word combinations based on the metadata. The method may also compare the metadata to rules wherein the rules determine if the message has unacceptable word combinations based on the metadata. The method may send the message to a user upon determining words in the message do not match any word in a list of unacceptable words.

Abstract: Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.

Abstract: Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.

Abstract: Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.

Abstract: Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.