A system, method, and computer-readable medium, including receiving a user-supplied expression for which a definition is sought; generating, in response to reception of the user-supplied expression, at least one suggested definition specifying a meaning for the user-supplied expression, the at least one suggested definition being generated based on, at least in part, a knowledge base of metadata associated with a data set; presenting the at least one suggested definition, as at least one keyword, to a user; receiving, in response to the presentation, an indication of one user-selected keyword from the at least one suggested definition; defining the user-selected keyword by at least one value; and persisting the defined user-selected keyword with the at least one value in the knowledge base for the data set.

A geolocation data discovery method, system, and non-transitory computer readable medium, include a secure text mining circuit configured to mine a textual alert message of an event from secure source data for a geolocational indicator, a temporal indicator, and a type of alert, a geolocation and temporal embedding circuit configured to embed a geolocational tag location and a temporal tag time to the event based on the geolocational indicator and the temporal indicator mined from the textual alert message by the secure text mining circuit, and an event mapping circuit configured to map the event with an icon related to the type of alert at the geolocational tag location on a navigational map at a time associated with the temporal tag time of the event.

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.

Mechanisms are provided for implementing a proximity based candidate answer pre-processor engine that outputs a sub-set of candidate answers to a question and answer (QA) system. The mechanisms receive a lexical answer type (LAT) and an entity specified in an input natural language question as well as an ontology data structure representing a corpus of natural language content. The mechanisms identify a set of candidate answers having associated nodes in the ontology data structure that are within a predetermined proximity of a node corresponding to the entity, and a sub-set of candidate answers in the set of candidate answers having an entity type corresponding to the LAT. The mechanisms output, to the QA system, the sub-set of candidate answers as candidate answers to the input natural language question for evaluation and selection of a final answer to the input natural language question.

A system and method for measuring a customer experience across a plurality of business channels in an organization has been provided. The system is configured to provide insight into customer experience across business channels from data generated via social media. The social media data of the customer pertaining to the organization is acquired and cleansed to obtain the unstructured data. Using linguistic and behavioral analysis of unstructured social data, the system enables an organization to understand customer experience by a plurality of channel to market, including the relationship of the channels on customer experience. Finally, it was concluded that whether the customer expectations are matched, missed or exceeded with the organization.

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.

Information may be presented to a user by using a first application to receive a character stream of one or more noncompletion characters. The noncompletion characters indicate that additional characters may be received. The character stream is exchanged with a host that analyzes the character stream to generate results that are responsive to the user's predicted interest. Results are received and displayed so that the user may select one of the results to launch a code segment related to the selected result.

Embodiments of the invention may be used to improve enforcement and compliance with publishing rules in an automated and provable manner. Prior to publication, documents may be processed using publishing rules (workflows) based on conceptual analysis of document content. Additionally, embodiments of the invention include a content creation system configured to provide prompt feedback on content coverage. Such a system enables the creator of information to better understand what approval requirements apply to content they create and intend to publish, as the content is being created.

A computer-implemented system and method for processing messages using native data serialization/deserialization without any transformation, in a service-oriented pipeline architecture is disclosed. The method in an example embodiment that includes serializing or deserializing the request/response message directly into the format (specific on-the-wire data format or a java object) the recipient expects (either a service implementation or a service consumer or the framework), without first converting into an intermediate format. This provides an efficient mechanism for the same service implementation to be accessed by exchanging messages using different data formats.