A computer-implemented method includes creating a classifier by: training a machine learning model using two or more tasks, wherein the tasks lie in two or more domains; including in the machine learning model at least one attribute common to at least two of said two or more domains; including in the machine learning model at least one latent feature that affects at least two of the two or more tasks that fall within one of the at least two domains; and constructing the classifier based on said machine learning model. The computer-implemented method further includes applying the classifier to at least one operational task.

Techniques are described for routing service requests in a computer-implemented service environment. A received service request may be initially analyzed to determine a priority of the request. In some implementations, one or more actions may be automatically performed to provide an initial response to the requester. The text of the request may be analyzed to automatically determine a category of the request. In some implementations, a classification engine may determine the category of the request through use of a classification model that has been trained using one or more machine learning (ML) techniques and/or that employs Natural Language Processing (NLP). Based on the category, the request may be routed to agent(s) for handling. Routing may include generating a ticket that includes the request, the category, the priority, and/or other information, and the ticket may be provided to the appropriate agent(s) through a ticketing service.

A computerized method of detecting product description inconsistencies, comprising receiving from a seller a product description comprising one or more attributes of a product offered for sale on an online marketplace arena, extracting automatically the one or more attributes by analyzing the product description using one or more language analysis tool, analyzing automatically the one or more attributes compared to a plurality of attributes of one or more other products of a same class as the product to detect one or more inconsistencies of the product description with respect to the one or more attributes and outputting the at least one inconsistency.

A method and apparatus utilized in operating a feedback forum in an online auction environment is described. Instead of allowing users of the system to enter freeform comments for and about other users, a number of predefined feedback comments are provided that relate to an auction transaction. Users leaving feedback for other users are permitted to select a comment they desire to leave for or about another user relative to a transaction. The predefined feedback comments selected by the users are associated with the users whom the comment is about, and at some time thereafter, the predefined feedback comment is displayed for viewing by other users of the system.

A method facilitates development of instructions in a precise syntax, such as software source code or built-in functions of a computational system, using natural language (NL) input. A user may enter NL input in a workspace. An NL processing system may process the NL input to generate instruction(s) in a precise syntax that corresponds to the NL input. The instruction(s) in the precise syntax then may be included in the workspace.

A method and/or computer program product validates a translation memory against terminology dictionary of a source and target language. For each source term, occurrences of a particular source term within source segments are identified, where an occurrence is determined according to grammar rules. For each identified source term occurrence in a source segment, a closeness score between a corresponding target term and a corresponding occurrence of the corresponding target term in a target segment is calculated. Each identified occurrence of a source term in a source segment is reported, as well as a closeness score, for each identified occurrence, between each identified occurrence and a corresponding target term in a target segment.

A quitting-intention estimating system facilitates detecting an entity's intention to quit an organization. During operation, the system obtains recent electronic-communication information associated with the entity under investigation, such as an employee of a corporation, or a volunteer of a non-profit organization. The system can determine the entity's quitting intention by determining a plurality of recent communication features from the electronic-communication information, for example, by using a variety of feature-extracting modules that extract the features from the entity's electronic communications. The system then computes a quitting-intention value for the entity under investigation, using a quitting-intention estimating function that takes the recent communication features as input. The quitting-intention estimating function detects a change in the entity's behavior from previous communication features, and generates a quitting-intention value which indicates a likelihood that the change in the entity's behavior corresponds to an intention to quit the organization.

A method for controlling a mobile terminal is provided. The method includes receiving content data including video data; determining whether first caption data including a first language caption is included in the content data; determining, if the first caption data is included in the content data, whether a high-difficulty word is included in the first language caption; generating explanation data corresponding to the high-difficulty word if the high-difficulty word is included in the first language caption; and converting the first caption data into second caption data by adding the explanation data to the first caption data.

Log files include log file content, some of which (especially a non-runtime portion) is in human-readable language. Translation of log file content is accomplished by: (i) generating first log content in a first human-readable language using a first resource bundle related to data translation; and (ii) translating the first log content to second log content, which corresponds to the first log content but is in a second human-readable language, using the first resource bundle. The translated log content may have annotations and/or processing rules applied to it. The translation of the present invention can help to keep the translation accurate and uniform so that the translated log content may be more effectively used in various ways.

Computer-implemented techniques can include receiving a selected word in a source language, obtaining one or more parts of speech for the selected word, and for each of the one or more parts-of-speech, obtaining candidate translations of the selected word to a different target language, each candidate translation corresponding to a particular semantic meaning of the selected word. The techniques can include for each semantic meaning of the selected word: obtaining an image corresponding to the semantic meaning of the selected word, and compiling translation information including (i) the semantic meaning, (ii) a corresponding part-of-speech, (iii) the image, and (iv) at least one corresponding candidate translation. The techniques can also include outputting the translation information.