Abstract:
A method includes receiving a corpus comprising a set of pre-segmented texts. The method further includes creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts and applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts. The method further includes clustering the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the one or more templates corresponds to one of the plurality of modified pre-segmented texts.
Abstract:
Disclosed aspects include initiating an electronic communication configured to be transmitted to a first intended recipient. Based on a set of profile data, a first cultural indicator may be identified for the first intended recipient. Using a natural language processing technique, a cultural element of the electronic communication may be detected. Based on both the first cultural indicator and the cultural element, a first cultural-version of the cultural element may be determined for the first intended recipient. Using the first cultural-version, a cultural translation object may be established in the electronic communication. In response to establishing the cultural translation object in the electronic communication, the electronic communication may be transmitted to the first intended recipient.
Abstract:
A computer-implemented method for language generation of a flow diagram, which receives a flow diagram. A plurality of geometric shapes within the flow diagram is identified. A plurality of text elements within the flow diagram is identified. The plurality of text elements and corresponding geometric shapes are associated. The association between the plurality of geometric shapes are identified. A diagram matrix based on the associations between the plurality of geometric shapes is generated. A linear language representation of the diagram matrix is generated.
Abstract:
The invention relates to a method for automatically detecting meaning patterns in a text using a plurality of input words, in particular a text with at least one sentence, comprising a database system containing words of a language, a plurality of defined categories of meaning in order to describe the properties of the words, and meaning signals for all the words stored in the database, wherein a meaning signal is a clear numerical characterization of the meaning of the words using the categories of meaning.
Abstract:
Examples are generally directed towards automatic assessment of machine generated conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of multi-reference responses. A response in the set of multi-reference responses includes it context-message data pair and rating. The rating indicates a quality of the response relative to the context-message data pair. A response assessment engine generates a metric score for a machine-generated response based on an assessment metric and the set of multi-reference responses. The metric score indicates a quality of the machine-generated conversational response relative to a user-generated message and a context of the user-generated message. A response generation system of a computing device, such as a digital assistant, is optimized and adjusted based on the metric score to improve the accuracy, quality, and relevance of responses output to the user.
Abstract:
A method of responding to a text-based communication on a portable electronic device includes receiving the text-based communication at the portable electronic device, performing textual analysis on the text-based communication to determine a set of possible responses, for each possible response of the set of possible responses, ranking the possible responses based at least on auxiliary information at the portable electronic device, and selecting a first possible response as a suggested response based on the ranking of the possible responses.
Abstract:
Embodiments of the present invention disclose a method, computer program product, and system for generating a plan for document processing. A plurality of electronic documents are received from a data store. The plurality of electronic documents are analyzed. Textual data within the identified tabular data are identified, by performing a first natural language search of the analyzed plurality of electronic documents. Textual hints are generated, where the generated textual hints are mapped to a lookup set. References are identified, and a count of identified references are determined. A priority score is calculating based on the count of identified references. In response to receiving a priority score modifying value, a modified priority score is calculated. Ingestion plans are generated based on the modified priority score. Generated ingestion plans are communicated by the computer using the network.
Abstract:
An information processing apparatus includes a selection unit selecting at least a part of a text included in contents, an acquisition unit acquiring a processing result of natural language processing for the part of the text selected by the selection unit, a specifying unit specifying a predetermined part of the text based on the processing result acquired by the acquisition unit, a detection unit detecting a keyword from the predetermined part of the text based on the processing result acquired by the acquisition unit, a tag generation unit automatically generating a tag in accordance with the keyword detected by the detection unit, and an association unit associating the tag generated by the tag generation unit with the predetermined part of the text.
Abstract:
Contact centers may incorporate automated agents to respond to inquiries. The inquiries may solicit a substantive response, for example, by providing a time when the inquiry asks for the departure time for a flight. Such responses omit the normal conversational subject matter used to embellish person-to-person conversations and appear are very machine-like. Herein, a source of user context, such as a social media website, customer database, or other data, is accessed. Certain aspects of the customer may then be identified and used to embellish the reply with additional and/or alternative content. As a result, the reply may be more conversational.
Abstract:
A method and system of expertise discovery in social networks accesses behavioral information associated with users' use of a computer-implemented social network, whereby the computer-implemented social network enables its users to have subscribing relationships with other users. Expertise levels of users of the social network with respect to one or more topics are automatically inferred from the behavioral information. The behavioral information may comprise interactions by other users with respect to content published by a user. The expertise levels of users may be inferred in accordance with the expertise levels of other users who are subscribed to them. Recommendations of users based on their expertise levels may be delivered, as well as explanations for the recommendations. Expertise levels of multiple users and/or expertise levels of a user over time may be delivered for display.