Abstract: Curation of a corpus of a cognitive computing system is performed by reporting to a user a cluster model of a parse tree structure of discrepancies and corresponding assigned confidence factors detected between at least a portion of a first electronic document and a second or more electronic documents in the information corpus. Responsive to a selection by the user of a discrepancy cluster model, drill-down details regarding the discrepancy are returned to the user, for subsequent user selection of an administrative action option for handling the detected discrepancy to curate the information corpus.

Abstract: A selected document from corpus of a cognitive computing system is processed according to its association with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the selected document and the other corpus documents. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A new document is processed for ingestion into a corpus of a cognitive computing system by associating with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the new document and those already in the corpus. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Abstract: Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Abstract: Curation of a corpus of a cognitive computing system is performed by reporting to a user a cluster model of a parse tree structure of discrepancies and corresponding assigned confidence factors detected between at least a portion of a first electronic document and a second or more electronic documents in the information corpus. Responsive to a selection by the user of a discrepancy cluster model, drill-down details regarding the discrepancy are returned to the user, for subsequent user selection of an administrative action option for handling the detected discrepancy to curate the information corpus.

Abstract: Curation of a corpus of a cognitive computing system is performed interactively by reporting on user interface device to a user a parse tree illustration of discrepancies and corresponding assigned confidence factors detected between at least a portion of a first document and a second or more documents in the corpus. Responsive to a user selection of an illustrated discrepancy in the parse tree, a drill-down dialog is prepared and displayed which shows at least a text string for the portion of the first document and at least one conflicting text string from the second or more documents, and which provides at least one user-selectable administrative action option for handling the detected discrepancy. Responsive to receipt of user selection of an administrative action option, the computing system performs the action to handle the detected discrepancy.

Abstract: A selected document from corpus of a cognitive computing system is processed according to its association with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the selected document and the other corpus documents. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A new document is processed for ingestion into a corpus of a cognitive computing system by associating with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the new document and those already in the corpus. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A selected document from corpus of a cognitive computing system is processed according to its association with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the selected document and the other corpus documents. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A new document is processed for ingestion into a corpus of a cognitive computing system by associating with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the new document and those already in the corpus. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Abstract: Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Abstract: Curation of a corpus of a cognitive computing system is performed interactively by reporting on user interface device to a user a parse tree illustration of discrepancies and corresponding assigned confidence factors detected between at least a portion of a first document and a second or more documents in the corpus. Responsive to a user selection of an illustrated discrepancy in the parse tree, a drill-down dialog is prepared and displayed which shows at least a text string for the portion of the first document and at least one conflicting text string from the second or more documents, and which provides at least one user-selectable administrative action option for handling the detected discrepancy. Responsive to receipt of user selection of an administrative action option, the computing system performs the action to handle the detected discrepancy.

Abstract: Curation of a corpus of a cognitive computing system is performed interactively by reporting on user interface device to a user a parse tree illustration of discrepancies and corresponding assigned confidence factors detected between at least a portion of a first document and a second or more documents in the corpus. Responsive to a user selection of an illustrated discrepancy in the parse tree, a drill-down dialog is prepared and displayed which shows at least a text string for the portion of the first document and at least one conflicting text string from the second or more documents, and which provides at least one user-selectable administrative action option for handling the detected discrepancy. Responsive to receipt of user selection of an administrative action option, the computing system performs the action to handle the detected discrepancy.

Abstract: A new document is processed for ingestion into a corpus of a cognitive computing system by associating with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the new document and those already in the corpus. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A system for storing a session cookie from another client application program, in which a separate client application is allowed to launch an external browser, and to supply a browser with a session cookie containing user specific session information. The browser is extended to support a new URI scheme providing for indication of a session cookie to be embedded into the browser, as well as an embedded URI to be processed by the browser after the indicated session cookie has been loaded into the browser. After the browser has been extended to handle the new URI scheme, a URI using the new scheme is passed to the browser as a command line parameter by a separate application program. The extended browser processes the new scheme URI, extracting the session cookie data and an embedded URI to be subsequently loaded. A client application separate from the browser may authenticate the user prior to the user requesting access to a secure Web page through the browser.