Abstract: An intelligent system and method for analyzing documents and suggesting corrections based on diversity criteria include a processing device to analyze a job document, using a machine learning model, to identify a first expression representing a first qualification requirement favorable to a first class of applicants than a second class of applicants according to a diversity metric, responsive to identifying the first expression, determine, using a semantic relation map, a second expression representing a second qualification requirement that is less favorable to the first class of applicants when compared to the first expression, and responsive to determining that the second expression, present the second expression on the interface device as a suggested replacement to the first expression in the job document.

Abstract: A computer-implemented method for fine-grained affective states prediction. The computer-implemented method creates training data comprising content conveying emotions. The method creates a trained model by performing an emotion vector space model training process using the training data to train a model using a feed forward neural network that converts discrete emotions into emotion vector representations. The trained model can be used to predict fine-grained affective states for text conveying an emotion.

Abstract: Systems and methods for domain classification in natural language processing based on domains are disclosed. The method includes generating a trigram corpus for the purpose of classification based on a trigram analysis of a domain model containing a hierarchical ontology and semantic construction that maps patterns of semantic tokens to syntactic patterns. An input string is parsed within each domain, tokenized in each domain. The resulting trigrams for the input text in each domain are looked up in the corresponding trigram corpus to determine the relevancy of each domain to the input text. The input string is thus classified based on the relevancy determination. The systems and methods avoids having to rely on existing annotated domain corpora for classification and allows for fast regeneration of the classifier when domain models are under frequent update and development.

Abstract: Systems for selective data capture and translation are provided. In some examples, a system, may receive data from one or more systems, networks, applications, devices, or the like. The data may include data associated with one or more issues occurring at the system, network, application, device, or the like. In some examples, a plurality of data containers may be generated. In some arrangements, each data container may be associated with a different issue, type of issue, system, application, or the like. The data containers may be generated in response to receiving data associated with an issue or may be pre-generated. In some arrangements, the received data may be evaluated (e.g., using machine learning) to determine whether it should be added to one or more data containers of the plurality of data containers. If so, the data may be added and, if not the data may be preserved and/or further evaluated to determine whether it should be added to a different data container.

Abstract: Provided is a method for providing a related application list on the basis of a message. An application list providing method according to an embodiment of the present invention, which is performed by an application list providing device, may comprise the steps of: receiving a provided message; determining a keyword on the basis of the message; determining an application list associated with the message by using the determined keyword, wherein the application list includes at least one application (APP); generating a deep link for at least one application included in the application list by using the determined keyword; and providing the application list and the deep link.

Abstract: A method for unsupervised language understanding may be carried out in a software environment and is operative to identify pairs of semantically-related words within a corpus of documents, extract candidate intents from the pairs of semantically-related words, and define the most general intents from the candidate intents, without human guidance or supervision.

Abstract: A scenario passage pair recognizer includes: a text passage searching unit searching a set of text passages each including no more than a certain number of sentences of a document, and within which all noun phrases included in a scenario candidate co-occur; a feature extracting unit extracting a feature from each combination of the scenario candidate and each searched support passage; a classifier outputting a score indicating reliability of the scenario candidate based on the support passage as a source of the feature; and a score accumulating unit and a maximum value selecting unit, accumulating the scores output from the classifier and selecting the maximum value as the reliability of the scenario candidate. The scenario classifier determines plausibility of the scenario candidate as a causality based on the feature including the score output from the scenario passage pair recognizer.

Abstract: Embodiments discussed herein refer to systems and methods for identifying relevantly similar sentiment in text strings.

Abstract: The present application discloses a method for presenting a virtual resource, a client, and a plug-in. The method includes: receiving a virtual resource associated with a piece of push information, and first text information associated with the push information from a server; presenting the first text information and prompt information, the prompt information prompting a user to input an audio data input to obtain the virtual resource; receiving audio data input by the user, obtaining an audio file data packet; uploading the audio data packet to the server for audio recognition; receiving second text information returned by the server, and determining an interaction result according to the first text information and the second text information; and presenting the virtual resource and sending a virtual resource activation acknowledgment message to the server based on the interaction result.

Abstract: A translation device includes an input unit and a controller. The input unit obtains first text data in a first language. The controller generates second text data in a second language that is a translation of the first text data. The controller further generates first replacement data by replacing a first term, of a predetermined type, contained in the first text data by a parameter, obtains second replacement data, in the second language, corresponding to the first replacement data, and generates the second text data by replacing the parameter contained in the second replacement data by a second term in the second language that is a translation of the first term.

Abstract: Techniques are disclosed to assist an author in creating content variations of a given input text to better suit the mood or the affect preferences of the target audience. Affect distribution in the content is utilized to capture these psycholinguistic preferences. According to one embodiment, in a first phase the optimal/idea psycholinguistic preference for text content aimed at a particular audience segment is determined. In a second phase, a given text content is modified to align to a target language distribution, which was determined in the first phase. In one example case, word level replacement, insertions and deletions are executed to generate a modified and coherent version of the input text. The output text thus reflects the psycholinguistic requirements of the audience.

Abstract: A method providing a computerized environment for human expert analyst community/ies including human expert analyst end users, including for at least one human expert analyst community: defining a prediction ontology stored in computer memory, including predetermined grammatical structure/s for predictions generated by human expert analysts in the community, the structure for conditional predictions including antecedent and consequence clauses; providing digitally represented analyst predictions, including individual analyst prediction/s expressed in the prediction ontology, being conditional, and associated with individual known network location/s from a universe thereof within the organization's computerized data network at which location, resource/s pertaining to the individual analyst prediction is stored; and generating and storing a uniform resource identifier-embedded prediction graph comprising: nodes which represent the analyst prediction's clauses, and at least one directional edge extending between

Abstract: A system is disclosed for providing an abstractive summary of a source textual document. The system includes an encoder, a decoder, and a fusion layer. The encoder is capable of generating an encoding for the source textual document. The decoder is separated into a contextual model and a language model. The contextual model is capable of extracting words from the source textual document using the encoding. The language model is capable of generating vectors paraphrasing the source textual document based on pre-training with a training dataset. The fusion layer is capable of generating the abstractive summary of the source textual document from the extracted words and the generated vectors for paraphrasing. In some embodiments, the system utilizes a novelty metric to encourage the generation of novel phrases for inclusion in the abstractive summary.

Abstract: An image processing apparatus includes a control unit that acts as: a searcher searching a first and second file, each including a text that is different in language from each other; a translator generating a translated text in the second file, by translating the text in the second file into a same language as a language of the text in the first file; a comparator comparing between the text in the first file and the translated text generated from the second file, and detecting a difference between the text in the first file and the text in the second file through comparison; and an outputter creating and outputting an image including both of the text in the first file and the text in the second file, with the difference detected by the comparator marked on the text in the first file or the text in the second file.

Abstract: A server system includes: a related word storage unit that stores information representing a relation between a plurality of registered words; a content storage unit that stores information about a content corresponding to any one of the plurality of words; a communication unit that acquires an input word; a related word search unit that searches for a related word, which is related to the acquired input word, by using the related word storage unit; and a content determination unit that provides a user with any of information about a content corresponding to the input word and information about a content corresponding to the related word.

Abstract: An approach to classify different defect records by mapping plain language phrases to a taxonomy. The approach includes a method that includes receiving, by at least one computing device, a defect record associated with a defect. The method further includes receiving, by the least one computing device, a plain language phrase or word. The method further includes mapping, by the least one computing device, the plain language phrase or word to a taxonomy. The method further includes classifying, by the least one computing device, how the defect was at least one of detected and resolved using the taxonomy.

Abstract: A call translation system and a method for operating the management system in a controlled environment is disclosed. The call translation system includes a calling device and a call translation server. The calling device receives authorization from the call translation server to conduct call sessions within the controlled environment. The calling device further receives a call session application from the call translation server that enables the calling device to initiate and establish call sessions through the call translation server. The call session application allows a user of the calling device to select outside parties to add to the call session.

Abstract: The present application discloses a method for presenting a virtual resource, a client, and a plug-in. The method includes: receiving a virtual resource associated with a piece of push information, and first text information associated with the push information from a server; presenting the first text information and prompt information, the prompt information prompting a user to input an audio data input to obtain the virtual resource; receiving audio data input by the user, obtaining an audio file data packet; uploading the audio data packet to the server for audio recognition; receiving second text information returned by the server, and determining an interaction result according to the first text information and the second text information; and presenting the virtual resource and sending a virtual resource activation acknowledgment message to the server based on the interaction result.

Abstract: Systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.

Abstract: A system and method for method and a system for mining rule intents from documents is provided, wherein the rule intents are basic atomic facts present in a sentence. The proposed method and system for mining of rule intents from documents is performed in multiple stages that include extraction of rule sentences from input documents that are further parsed to create dependency trees. The created dependency trees are further analyzing based on a set of plurality of heuristic rules to mine rule intents. The mined rule intents are saved and further displayed in Semantics of Business Vocabulary and Rules (SBVR) format. The mined rule intents that are displayed automatically in the SBVR format can be easily analyzed as they SBVR is a comprehensive standard for business rule representation by Object Management Group (OMG) in accordance with set of a standard pre-defined vocabularies.