An embodiment may involve a database containing a first user profile that specifies a first preferred language of a first user and a second user profile that specifies a second preferred language of a second user. The embodiment may also involve one or more processors configured to: receive, from the first user and within a chat session, a first set of messages in the first preferred language; cause the first set of messages to be translated into the second preferred language; provide, to the second user and within the chat session, the first set of messages as translated; receive, from the second user and within the chat session, a second set of messages in the second preferred language; cause the second set of messages to be translated into the first preferred language; and provide, to the first user and within the chat session, the second set of messages as translated.

A content management system provides a mechanism for multi-file check-in features useful for content management. The content management system provides a way for users to check in multiple files in a single action. The system allows users to either select assets (e.g., files) or drag and drop multiple assets to be checked in. The assets being checked in are automatically matched with checked out assets, and once matched, unlocked.

Provided are a method and apparatus for constructing a compact translation model that may be installed on a terminal on the basis of a pre-built reference model, in which a pre-built reference model is miniaturized through a parameter imitation learning and is efficiently compressed through a tree search structure imitation learning without degrading the translation performance. The compact translation model provides translation accuracy and speed in a terminal environment that is limited in network, memory, and computation performance.

An apparatus includes a data access circuit that interprets data records, each having a number of data fields, a record parsing circuit that determines a number of n-grams from terms of each of the data records and maps the number of n-grams to a corresponding number of mathematical vectors, and a record association circuit that determines whether a similarity value between a first mathematical vector for the first data record and a second mathematical vector for the second data record is greater than a threshold similarity value, and associates the first and second data records in response to the similarity value exceeding the threshold similarity value. An example apparatus includes a reporting circuit that provides a catalog entity identifier, associates each of the first term and the second term to the catalog entity identifier, and provides a summary of activity for an entity.

A method includes: acquiring an input sentence in a first language in a current round of conversation; translating the input sentence in the first language to obtain an input sentence in a second language, according to dialogue contents in the first language and dialogue contents in the second language that have a mutual translation relationship with the dialogue contents in the first language in historical rounds of conversation; invoking a multi-round conversation generation model to parse the input sentence in the second language in the current round of conversation to generate an output sentence in the second language in the current round of conversation; translating the output sentence in the second language in the current round of conversation to obtain at least one candidate result in the first language; and determining an output sentence in the first language from the at least one candidate result in the first language.

A method includes obtaining a query in a base language and translating the query to generate one or more translated queries each in a respective target language. The method also includes searching one or more sets of electronic files based on the one or more translated queries to generate target-language search results, where each translated query is used to search one or more electronic files that include content in the respective target language of the translated query. The method also includes, based on the target-language search results, scheduling one or more electronic files of the one or more sets of electronic files for at least partial translation to the base language.

A non-transitory computer-readable recording medium stores an information searching program causing a computer to execute processing of: in an information search using a trained machine learning model generated by machine learning using training data in a first language, when a search condition is in the first language, translating the search condition to a second language different from the first language; re-translating the search condition translated to the second language to the first language; and performing the information search by inputting the search condition re-translated to the first language to the machine learning model; and when the search condition is in a language different from the first language, translating the search condition to the first language, and performing the information search by inputting the search condition translated to the first language to the machine learning model.

A non-transitory computer-readable recording medium stores an information generating program causing a computer to execute processing of: in an information search using a trained machine learning model generated by machine learning using training data in a first language, converting a search condition in a second language different from the first language to the search condition in the first language; searching information in the first language by inputting the search condition converted to the first language to the machine learning model; and generating training data with the search condition converted to the first language as a feature value and the searched information in the first language as a correct answer label.

A system and method for providing a response to at least one code-mix user query on a digital platform. The method encompasses receiving, by a transceiver unit, the at least one code-mix user query at the digital platform. The method thereafter comprises translating dynamically, by a translation engine, the at least one code-mix user query in a first language based on a pre-trained and fine-tuned sub-system, wherein: the sub-system is pre-trained based on a pre-existing first language corpus, and the sub-system is fine-tuned based on a parallel corpus of one or more pre-existing code-mix user queries. Further the method encompasses identifying and providing, by a response generator, the response to the at least one code-mix user query based at least on the dynamic translation of the at least one code-mix user query.

An embodiment may involve a database containing a first user profile that specifies a first preferred language of a first user and a second user profile that specifies a second preferred language of a second user. The embodiment may also involve one or more processors configured to: receive, from the first user and within a chat session, a first set of messages in the first preferred language; cause the first set of messages to be translated into the second preferred language; provide, to the second user and within the chat session, the first set of messages as translated; receive, from the second user and within the chat session, a second set of messages in the second preferred language; cause the second set of messages to be translated into the first preferred language; and provide, to the first user and within the chat session, the second set of messages as translated.