Abstract:
A computer-implemented method for cognitive matching of narrative data may include collecting a set of data for a party and determining, by analyzing the set of data, an identifiable event for the party. In addition, the method may include identifying, using the identifiable event, a relevant feature of a corpus and providing an output corresponding to the relevant feature.
Abstract:
A method, computer system, and computer program product for cognitively coaching a user to take favorable photographs are provided. The embodiment may include determining characteristics of favorable photographs from a favorable photo database using image analysis techniques. The embodiment may also include identifying subjects in a current camera frame. The embodiment may further include identifying characteristics of a photograph from a current camera frame. The embodiment may also include determining similarities or differences between the favorable photographs and the current camera frame. The embodiment may further include generating directions that map a current state of similar characteristics to the favorable photographs.
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:
At least one physical object located in a real world environment in which a user physically is located can be detected using at least one sensor. Coordinates of where the physical object is located relative to the user in the real world environment can be determined. A virtual object can be presented in a virtual reality environment at virtual coordinates, relative to a virtual representation of the user in the virtual reality environment, corresponding to the determined real world environment coordinates of where the physical object is located relative to the user in the real world environment.
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, 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 cognitive matching of narrative data mechanism may include a collecting module configured to collect a set of data for a party and a determining module configured to determine, by analyzing the set of data, an identifiable event for the party. The mechanism may include may also include an identifying module configured to identify, using the identifiable event, a relevant feature of a corpus, and a providing module configured to provide an output corresponding to the relevant feature.
Abstract:
First, a computer may receive an input query of a first medium type. The input query may then be analyzed. Based on the analysis, the input query may be categorized as being associated with at least a second medium type. A first-medium-type search of a set of corpora may then be performed. Based on the results of the first-medium-type search, a candidate answer of the first medium type may be generated. In response to the categorizing, a second-medium-type search of the set of corpora may also be performed.
Abstract:
In some NLP systems, queries are compared to different data sources stored in a corpus to provide an answer to the query. However, the best data sources for answering the query may not currently be contained within the corpus or the data sources in the corpus may contain stale data that provides an inaccurate answer. When receiving a query, the NLP system may evaluate the query to identify a data source that is likely to contain an answer to the query. If the data source is not currently contained within the corpus, the NLP system may ingest the data source. If the data source is already within the corpus, however, the NLP may determine a time-sensitivity value associated with at least some portion of the query. This value may then be used to determine whether the data source should be re-ingested—e.g., the information contained in the corpus is stale.
Abstract:
System, computer-implemented method, and computer program product to receive a case by a deep question answering system, identify a policy relevant in generating a response to the case, the policy containing a set of criteria used in generating the response to the case, produce, by a first annotator, of a set of annotators, one or more relevant passages of the case, compute a criteria score for a first criterion, of the set of criteria, based on the one or more relevant passages of the case, an determine that the first criterion is met by the case when the criteria score for the first criterion exceeds a predefined threshold.