Abstract: A system, a method, and a computer program product for managing answer feasibility in a Question and Answering (QA) system. A set of candidate situations is established. The set of candidate situations corresponds to a first set of answers. A QA system establishes the set of candidate situations by analyzing a corpus. The first set of answers will answer a question. The QA system identifies a subset of the set of candidate situations. The subset of candidate situations corresponds to a portion of contextual data. The portion of contextual data is from a set of contextual data. The set of contextual data relates to the question. The question-answering system determines a set of answer feasibility factors. The set of answer feasibility factors is determined using the subset of candidate situations. The set of answer feasibility factors indicates the feasibility of the answers in the first set of answers.

Abstract: A system and computer implemented method for managing perspective data is disclosed. The method may include collecting a first lot of perspective data for an item. The method may include introducing a variant feature to the item to constitute a modified item. The method may include collecting a second lot of perspective data for the modified item. The method may also include evaluating the first and second lots of perspective data to ascertain a sentiment fluctuation based on information relevant to the variant feature.

Abstract: The program matches a VR environment of a user with an optimal physical location. The method loads a VR program, and detects at least one location-based goal of the user based on a virtual environment of the VR program. The method determines if a current location of the user is an optimal physical location for the at least one location-based goal of the user, based on a plurality of determined criteria associated with the current location and the determined virtual environment associated with the VR program. The method searches for an optimal physical location based on at least one location-based goal of the user and matches the optimal physical location of the user with the at least one location-based goal of the user in the VR program based on the plurality of determined criteria associated with the optimal physical location and the determined virtual environment associated with the VR program.

Abstract: A processor uses natural language processing to ingest product reviews for a plurality of products. Each of the products embodies a specific form for each of the plurality of product features. The processor analyzes the ingested product reviews for sentiments associated with the specific forms. The processor generates a sentiment score for each product feature based on the analysis. The processor ranks the plurality of product features based on the sentiment scores.

Abstract: The program matches a VR environment of a user with an optimal physical location. The method loads a VR program, and detects at least one location-based goal of the user based on a virtual environment of the VR program. The method determines if a current location of the user is an optimal physical location for the at least one location-based goal of the user, based on a plurality of determined criteria associated with the current location and the determined virtual environment associated with the VR program. The method searches for an optimal physical location based on at least one location-based goal of the user and matches the optimal physical location of the user with the at least one location-based goal of the user in the VR program based on the plurality of determined criteria associated with the optimal physical location and the determined virtual environment associated with the VR program.

Abstract: Software that generates list items from user conversations by performing the following operations: (i) capturing natural language statement(s) spoken by a first user; (ii) converting the natural language statement(s) to text; (iii) performing a natural language processing (NLP) analysis of the text to identify a first list item, wherein the first list item includes one or more words in the text that are likely to be included in a list associated with the first user; and/or performing a first list action utilizing the first list item based, at least in part, on the performed NLP analysis, wherein the first list action includes modifying a first list associated with the first user.

Abstract: A processor uses natural language processing to ingest product reviews for a plurality of products. Each of the products embodies a specific form for each of the plurality of product features. The processor analyzes the ingested product reviews for sentiments associated with the specific forms. The processor generates a sentiment score for each product feature based on the analysis. The processor ranks the plurality of product features based on the sentiment scores.

Abstract: A first question may be received. A first tag may be identified. The first tag may correspond to a first demographic trait. The first tag may be for use in providing a context for generating a first answer estimate to the first question. The first answer estimate may be generated using natural language processing and based on the first tag.

Abstract: A computer system may obtain a first knowledge graph that was generated based on a work of authorship having a plurality of narrative blocks. The computer system may identify target narrative blocks, which are narrative blocks that include a target concept. The computer system may also identify related background narrative blocks. The computer system may receive a narrative path for the target concept. The narrative path may include the target narrative blocks and the related background narrative blocks ordered in a sequence that is consistent with their order in the work of authorship. The computer system may output the narrative path to an output device coupled with the computer system.

Abstract: Embodiments herein include a natural language computing system that provides a diagnosis for a participant in the conversation which indicates the likelihood that the participant exhibited a symptom of autism. To provide the diagnosis, the computing system includes a diagnosis system that performs a training process to generate a machine learning model which is then used to evaluate a textual representation of the conversation. For example, the diagnosis system may receive one or more examples of baseline conversations that exhibit symptoms of autisms and those that do not. The diagnosis system may annotate and the baseline conversations and identify features that are used to identify the symptoms of autism. The system generates a machine learning model that weights the features according to whether the identified features are, or are not, an indicator of autism.

Abstract: Embodiments herein include a natural language computing system that provides a diagnosis for a participant in the conversation which indicates the likelihood that the participant exhibited a symptom of autism. To provide the diagnosis, the computing system includes a diagnosis system that performs a training process to generate a machine learning model which is then used to evaluate a textual representation of the conversation. For example, the diagnosis system may receive one or more examples of baseline conversations that exhibit symptoms of autisms and those that do not. The diagnosis system may annotate and the baseline conversations and identify features that are used to identify the symptoms of autism. The system generates a machine learning model that weights the features according to whether the identified features are, or are not, an indicator of autism.

Abstract: A content management system (CMS) autonomically generates structure for a document when a synchronization rule references structure that does not exist in the document. A dynamic structure policy specifies at least one criterion that determines if and how the structure is autonomically generated. By autonomically generating structure in a document, a CMS administrator or CMS user (such as the author) is relieved of the manual task of generating the structure before the synchronization rule can be successfully processed. Once dynamically generated, the added structure may be auto-populated with dummy data or with default data specified in the autonomic structure policy.

Abstract: Aspects of the present disclosure are directed toward discovering and generating answer sequences. Aspects are directed toward parsing, by a natural language processing technique configured to analyze syntactic and semantic content, a corpus of data for a subject matter. Aspects are also directed toward detecting a first set of answers including a first answer corresponding to a first answer category and a second set of answers including a second answer corresponding to a second answer category. Both the first and the second answer categories may relate to the subject matter. Aspects are also directed toward identifying a first set of ordering data for the first set of answers and the second set of answers. Aspects are also directed toward determining a first answer sequence corresponding to an order of the first set of answers and the second set of answers.

Abstract: Techniques disclose methods for providing voice-based web navigation through a cellular voice connection. A voice command a request to return content of a webpage having one or more topics is received via a cellular voice connection. One or more of the topics of the webpage that match the content specified in the request is identified. An audio indication of the content is returned via the cellular voice connection.

Abstract: Techniques disclose methods for providing voice-based web navigation through a cellular voice connection. A voice command a request to return content of a webpage having one or more topics is received via a cellular voice connection. One or more of the topics of the webpage that match the content specified in the request is identified. An audio indication of the content is returned via the cellular voice connection.

Abstract: System, method, and computer program product for performing an operation, the operation comprising receiving, by a deep question answering system, a question not specifying an element of input data, identifying a set of possible values for the element of input data, generating, by the deep question answering system, a respective set of candidate answers for the question: (i) without the element of input data, and (ii) with each possible value in the set of possible values for the element of input data, and returning at least one candidate answer from at least one set of candidate answers as responsive to the question.

Abstract: System, method, and computer program product for performing an operation, the operation comprising receiving, by a deep question answering system, a question not specifying an element of input data, identifying a set of possible values for the element of input data, generating, by the deep question answering system, a respective set of candidate answers for the question: (i) without the element of input data, and (ii) with each possible value in the set of possible values for the element of input data, and returning at least one candidate answer from at least one set of candidate answers as responsive to the question.

Abstract: A system and computer-implemented method for managing perspective data is disclosed. The method may include identifying a variant feature of an item having a first set of perspective data. The method may include grouping, based on the variant feature, the first set of perspective data into a first group and a second group. The method may include determining a first set of relevancy scores for the first group and a second set of relevancy scores for the second group. The method may also include establishing, using at least one of the first and second relevancy scores, a second set of perspective data configured to include a subset of the first set of perspective data.

Abstract: A system and computer-implemented method for managing perspective data is disclosed. The method may include identifying a variant feature of an item having a first set of perspective data. The method may include grouping, based on the variant feature, the first set of perspective data into a first group and a second group. The method may include determining a first set of relevancy scores for the first group and a second set of relevancy scores for the second group. The method may also include establishing, using at least one of the first and second relevancy scores, a second set of perspective data configured to include a subset of the first set of perspective data.

Abstract: Method to perform an operation comprising receiving, from a set of input devices, data of an environment surrounding a computing device, determining a current context of a discussion based on the data and a timing schedule specifying a list of planned contexts, receiving a request to perform an operation on the computing device, determining a context of the requested operation, determining a measure of relatedness between the contexts, and upon determining the measure of relatedness does not exceed a predefined threshold, restricting execution of the operation.