Abstract: A method and system are provided for implementing enhanced cognitive searches optimized to integrate deployment with development testing. An initial body of works is ingested into a system capable of answering questions. A series of queries is analyzed against the initial body of works utilizing a set of scorers utilizing criteria to form assessments, wherein each scorer uses the criteria against the query and the initial body of works to form the assessment. The assessments are analyzed to determine a usefulness of a set of entries in the initial body of works. Content are deployed using the identified selected first set of entries as deployment ready, enabling enhanced cognitive search results.

Abstract: A method, computer system, and computer program product for form-based conversation system design are provided. The embodiment may include ingesting, by a processor, a plurality of forms from a given domain. The embodiment may also include extracting indicators of required input fields from the ingested plurality of forms. The embodiment may further include generating a required input list based on the extracted indicators of the required input fields to update a size of the required input list. The embodiment may also include determining transactional intents based on the required input list. The embodiments may further include generating a dialog flow that satisfies the determined transactional intents.

Abstract: A method for form-based conversation system design is provided. The embodiment may include ingesting, by a processor, a plurality of forms from a given domain. The embodiment may also include extracting indicators of required input fields from the ingested plurality of forms. The embodiment may further include generating a required input list based on the extracted indicators of the required input fields to update a size of the required input list. The embodiment may also include determining transactional intents based on the required input list. The embodiments may further include generating a dialog flow that satisfies the determined transactional intents.

Abstract: Mechanisms for evaluating an evidential statement in a corpus of evidence are provided. A first evidential statement for which corroboration is sought is received and a corpus of evidence data is processed to determine a measure of corroboration of the first evidential statement by other evidence data in the corpus of evidence data. An indication of trustworthiness of the first evidential statement is generated based on the measure of corroboration of the first evidential statement by the other evidence data in the corpus of evidence data. A representation of the indication of the trustworthiness of the first evidential statement is output in association with the first evidential statement.

Abstract: Mechanisms for evaluating an evidential statement in a corpus of evidence are provided. An evidential statement is received for determining a level of confidence in a hypothetical ontological link of an ontology. A source of the evidential statement is identified and a grading of the source of the evidential statement is determined based on a source grading measurement value indicative of a degree of reliability and credibility of the source. An indication of trustworthiness of the evidential statement is generated based on the source grading measurement value. A representation of the indication of trustworthiness of the evidential statement is output in association with the evidential statement.

Abstract: An approach is provided in which an information handling system performs multiple tests using a cognitive service and multiple trained machine learning models on user data corresponding to a user application. For each of the multiple tests, a different one of the trained machine learning models is utilized. The information handling system generates results from the tests and then selects at least one of the trained machine learning models based on the test results. In turn, the information handling system assigns the cognitive service and the selected trained machine learning models to the user application.

Abstract: Provided are techniques for OCR induction for multi-page changes. A plurality of documents of a document type are processed to generate text area data for a text area in one or more documents of the plurality of documents, where the text area data includes coordinate locations of a zone for the text area based on expansion and direction of shift of the text area. A page flow model is trained using the plurality of documents and the text area data. In response to receiving a new document comprising the text area, a scanning script is received from the page flow model, where the page flow model identifies a new zone for the text area in the new document and determines how to adjust another zone for an element in the new document. The scanning script is used to scan the new document to generate digital text.

Abstract: Mechanisms, in a Question Answering (QA) system comprising a processor and a memory, for evaluating a hypothetical link in an ontology are provided. An initial analysis of the ontology is performed to identify a set of information concept entities and links between information concept entities in the ontology. The hypothetical link between a first information concept entity and a second information concept entity in the ontology is generated based on the initial analysis of the ontology. Natural language questions corresponding to the hypothetical link are processed to generate answer results directed to a plurality of links between a plurality of information concept entities. The answer results are aggregated across the plurality of links to determine an aggregate answer result for the hypothetical link. An indication of whether or not the hypothetical link is a valid link is output based on the aggregate answer result for the hypothetical link.

Abstract: In one general embodiment, a computer-implemented method includes identifying an input search term, determining an additional term associated with the input search term, where the additional term targets a predetermined entity, altering the input search term utilizing the determined additional term, and performing a search, utilizing the altered input search term.

Abstract: A technique for caching evidence for answering questions in a cache memory of a data processing system (that is configured to answer questions) includes receiving a first question. The first question is analyzed to identify a first set of characteristics of the first question. A first set of evidence for answering the first question is loaded into the cache memory. A second question is received. The second question is analyzed to identify a second set of characteristics of the second question. A portion of the first set of evidence, whose expected usage in answering the second question is below a determined threshold, is unloaded from the cache memory.

Abstract: An approach is disclosed for building a study cohort by collecting information related to a plurality of people according to a collection request from a user. An authority of the request from the user is validated and if validated, a file policy associated with each file containing personal data is checked to verify a type of processing consented by the corresponding individual for their data. The data is transformed, and information copied related to the plurality of people according to the collection request, the request assessment, the consent information as part of each file's metadata, and the privacy legal framework. The privacy legal framework is enforced by the OS and may be based on source files wherein each source file has a source file consent permission to form copied content. The copied content is used to process the collection request.

Abstract: Mechanisms are provided in a data processing system for utilizing algorithms based on categories in a question answering system. The mechanisms capture a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to questions in respective question categories in a question answering system. The mechanisms determine sets of algorithms to use for respective question categories according to efficiency and correctness analysis. The mechanisms determine a question category of a given input question and execute a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question.

Abstract: Mechanisms are provided that generate a knowledge data structure for a medical condition. The mechanisms parse a natural language positional statement data structure representing a natural language positional statement corresponding to a medical condition, where the natural language positional statement specifies guidance information and patient attributes indicative of patients for which an action may be performed for the medical condition. The mechanisms extract the patient attributes and a grading value associated with the natural language positional statement. The mechanisms generate at least one weight value associated with each of the patient attributes based on the grading value.

Abstract: A technique for caching evidence for answering questions in a cache memory of a data processing system (that is configured to answer questions) includes receiving a first question. The first question is analyzed to identify a first set of characteristics of the first question. A first set of evidence for answering the first question is loaded into the cache memory. A second question is received. The second question is analyzed to identify a second set of characteristics of the second question. A portion of the first set of evidence, whose expected usage in answering the second question is below a determined threshold, is unloaded from the cache memory.

Abstract: A method, system and computer-usable medium are disclosed for using table-based groundtruth to train a question-answer (QA) system, comprising: receiving a corpus of text comprising unstructured text and a table; performing QA pair generation operations on the unstructured text and the table to generate QA pairs, the QA pairs being based upon information obtained from the table; assigning a score to each QA pair, the score corresponding to an indicator of user interest.

Abstract: A method for creating content includes making a corpus of images available, adding a plurality of tag data to each of the images, receiving a query, extracting a trigger from the query, identifying a set of the images in the corpus, wherein identified images have tag data matching the extracted trigger, and creating a video comprising the identified images.

Abstract: Mechanisms are provided for implementing a disambiguation engine for disambiguating content. Electronic content is received from a corpus of electronic content, and analyzed to identify an ambiguous portion of content. The ambiguous portion of content is a portion of the electronic content whose meaning is not made explicit in the ambiguous portion of content. A context associated with the ambiguous portion of content is determined and a set of one or more context based ambiguous content interpretation rules associated with the determined context is applied to the ambiguous portion of content to generate an interpretation of the ambiguous portion of content. The ambiguous portion of content is annotated based on the interpretation to generate disambiguated electronic content which is stored for processing as part of a subsequent operation.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: A method is provided for categorizing a problem report in a repository of a problem reporting system as an enhancement request or as a defect. Based on the problem report being the defect and having a high severity level, determining a score indicating a probability that a text portion of the problem report includes problem reproduction steps. In response to the score indicating the probability of problem reproduction steps, flagging the problem report to automate. For each problem report to automate, copying the text portion of the problem report to an automated test script, whereby the test script runs in a continuous pipeline.

Abstract: Aspects of the present disclosure relate to identifying semantic relationships. Natural language content is received. A part of speech is determined for respective terms within the natural language content. A semantic type is determined for each of two or more terms within the natural language content. A parse tree representation containing a plurality of nodes is then generated based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms. A bounding box identifying a semantic relationship is then generated around a set of nodes on the parse tree representation, the set of nodes including the two or more terms.