Abstract: Disclosed aspects relate to generating rationales for treatment options. A set of preference scores that indicates a first preference score for a first treatment option of a set of treatment options may be received. A rank-order that indicates a first ranking for the first treatment option may be received. The set of preference scores may be analyzed with respect to the rank-order to determine a relationship between the first preference score and the first ranking for the first treatment option. Based on the relationship between the first preference score and the first ranking, a set of rationale data for the first treatment option may be generated with respect to the first rank. Based on a user profile for a user, the set of rationale data may be configured for the user. The set of rationale data which is configured for the user may be provided.

Abstract: Methods to, responsive to receiving a case by a deep question answering (deep QA) system, identify, in a corpus of information, a first variable for which a value was not specified in the case, compute an importance score for the first variable based on a concept in the corpus, wherein the concept is associated with the first variable, and upon determining that the importance score exceeds an importance threshold, determine that specifying a value for the first variable increases a confidence score of a response returned by the deep QA system beyond a confidence threshold.

Abstract: Systems and computer program products to, responsive to receiving a case by a deep question answering (deep QA) system, identify, in a corpus of information, a first variable for which a value was not specified in the case, compute an importance score for the first variable based on a concept in the corpus, wherein the concept is associated with the first variable, and upon determining that the importance score exceeds an importance threshold, determine that specifying a value for the first variable increases a confidence score of a response returned by the deep QA system beyond a confidence threshold.

Abstract: Systems and computer program products to perform an operation comprising: identifying a first attribute of a source code in a deep question answering system, computing an influence score for the first attribute based on a rule in the source code used to compute a confidence score for each of a plurality of candidate answers generated by the deep question answering system, computing an importance score for the first attribute based at least in part on the computed influence score, and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first attribute is an important attribute relative to other attributes specified in the source code.

Abstract: Disclosed aspects relate to generating rationales for treatment options. A set of preference scores that indicates a first preference score for a first treatment option of a set of treatment options may be received. A rank-order that indicates a first ranking for the first treatment option may be received. The set of preference scores may be analyzed with respect to the rank-order to determine a relationship between the first preference score and the first ranking for the first treatment option. Based on the relationship between the first preference score and the first ranking, a set of rationale data for the first treatment option may be generated with respect to the first rank. Based on a user profile for a user, the set of rationale data may be configured for the user. The set of rationale data which is configured for the user may be provided.

Abstract: Methods to perform an operation comprising: identifying a first attribute of a source code in a deep question answering system, computing an influence score for the first attribute based on a rule in the source code used to compute a confidence score for each of a plurality of candidate answers generated by the deep question answering system, computing an importance score for the first attribute based at least in part on the computed influence score, and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first attribute is an important attribute relative to other attributes specified in the source code.

Abstract: Disclosed aspects relate to generating rationales for treatment options. A set of preference scores that indicates a first preference score for a first treatment option of a set of treatment options may be received. A rank-order that indicates a first ranking for the first treatment option may be received. The set of preference scores may be analyzed with respect to the rank-order to determine a relationship between the first preference score and the first ranking for the first treatment option. Based on the relationship between the first preference score and the first ranking, a set of rationale data for the first treatment option may be generated with respect to the first rank. Based on a user profile for a user, the set of rationale data may be configured for the user. The set of rationale data which is configured for the user may be provided.

Abstract: System, method, and computer program product to identify candidate values to provide to a deep question answering (QA) system as part of a case, by receiving a case, wherein the case includes a plurality of documents for evaluation by the deep QA system, evaluating the plurality of documents using natural language processing (NLP) to identify one or more concepts reflected by text content within the plurality of documents in the case, wherein the plurality of documents includes a plurality of distinct values for at least a first one of the concepts, selecting, from the plurality of distinct values, a candidate value for the first concept to provide to the deep QA system to process the case, and prior to submitting the case to the deep QA system, returning at least the candidate value selected for the first concept to present in a user interface.

Abstract: Managing confidence data in a question-answering environment is disclosed. Managing confidence data can include sorting, based on a set of answer categories for a subject matter, a first set of a plurality of answers into a first answer category. The first set can correspond to at least one of a third set of a plurality of confidence scores and the second set can correspond to at least one of a fourth set of the plurality of confidence scores. Managing confidence data can include classifying confidence scores of the third set into one of a plurality of confidence buckets using a first threshold and determining a fifth set of a plurality of thresholds using the plurality of confidence scores. Managing confidence data can include classifying unclassified confidence scores of the third set into one of the plurality of confidence buckets using the fifth set of the plurality of thresholds.

Abstract: Managing confidence data in a question-answering environment is disclosed. Managing confidence data can include sorting, based on a set of answer categories for a subject matter, a first set of a plurality of answers into a first answer category. The first set can correspond to at least one of a third set of a plurality of confidence scores and the second set can correspond to at least one of a fourth set of the plurality of confidence scores. Managing confidence data can include classifying confidence scores of the third set into one of a plurality of confidence buckets using a first threshold and determining a fifth set of a plurality of thresholds using the plurality of confidence scores. Managing confidence data can include classifying unclassified confidence scores of the third set into one of the plurality of confidence buckets using the fifth set of the plurality of thresholds.

Abstract: A computer program product in one embodiment a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method that includes establishing, by the computer, communication between a master node and several federated nodes, where each node is an instance of a distributed application; initialize, by the computer, the distributed application, where the initialization includes the federated nodes processing data local thereto and providing information about the local data to the master node; and after initialization, at run time, receive, by the computer, data requests, where the master node services the data requests by routing the requests to the nodes.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria in unstructured and semi-structured data within a form. Text spans representing unchecked criteria within unstructured text in a form are detected and classified to facilitate accurate interpretation of the text. Section identification and annotation operations are then performed to identify and categorize sections within the form. Checklist sections within the form, along with associated checkmarks and boxes, are then identified, followed by the identification of checked item, criteria scope, and previously undetected checklist sections. Once all checklist sections and checked criteria have been identified, remaining text spans within a checklist section are annotated as unchecked criteria.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria in unstructured and semi-structured data within a form. Text spans representing unchecked criteria within unstructured text in a form are detected and classified to facilitate accurate interpretation of the text. Section identification and annotation operations are then performed to identify and categorize sections within the form. Checklist sections within the form, along with associated checkmarks and boxes, are then identified, followed by the identification of checked item, criteria scope, and previously undetected checklist sections. Once all checklist sections and checked criteria have been identified, remaining text spans within a checklist section are annotated as unchecked criteria.

Abstract: System, method, and computer program product to identify candidate values to provide to a deep question answering (QA) system as part of a case, by receiving a case, wherein the case includes a plurality of documents for evaluation by the deep QA system, evaluating the plurality of documents using natural language processing (NLP) to identify one or more concepts reflected by text content within the plurality of documents in the case, wherein the plurality of documents includes a plurality of distinct values for at least a first one of the concepts, selecting, from the plurality of distinct values, a candidate value for the first concept to provide to the deep QA system to process the case, and prior to submitting the case to the deep QA system, returning at least the candidate value selected for the first concept to present in a user interface.

Abstract: Systems and computer program products to perform an operation comprising: identifying a first attribute of a source code in a deep question answering system, computing an influence score for the first attribute based on a rule in the source code used to compute a confidence score for each of a plurality of candidate answers generated by the deep question answering system, computing an importance score for the first attribute based at least in part on the computed influence score, and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first attribute is an important attribute relative to other attributes specified in the source code.

Abstract: Methods to perform an operation comprising: identifying a first attribute of a source code in a deep question answering system, computing an influence score for the first attribute based on a rule in the source code used to compute a confidence score for each of a plurality of candidate answers generated by the deep question answering system, computing an importance score for the first attribute based at least in part on the computed influence score, and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first attribute is an important attribute relative to other attributes specified in the source code.

Abstract: Methods to, responsive to receiving a case by a deep question answering (deep QA) system, identify, in a corpus of information, a first variable for which a value was not specified in the case, compute an importance score for the first variable based on a concept in the corpus, wherein the concept is associated with the first variable, and upon determining that the importance score exceeds an importance threshold, determine that specifying a value for the first variable increases a confidence score of a response returned by the deep QA system beyond a confidence threshold.

Abstract: Systems and computer program products to, responsive to receiving a case by a deep question answering (deep QA) system, identify, in a corpus of information, a first variable for which a value was not specified in the case, compute an importance score for the first variable based on a concept in the corpus, wherein the concept is associated with the first variable, and upon determining that the importance score exceeds an importance threshold, determine that specifying a value for the first variable increases a confidence score of a response returned by the deep QA system beyond a confidence threshold.

Abstract: Managing confidence data in a question-answering environment is disclosed. Managing confidence data can include sorting, based on a set of answer categories for a subject matter, a first set of a plurality of answers into a first answer category. The first set can correspond to at least one of a third set of a plurality of confidence scores and the second set can correspond to at least one of a fourth set of the plurality of confidence scores. Managing confidence data can include classifying confidence scores of the third set into one of a plurality of confidence buckets using a first threshold and determining a fifth set of a plurality of thresholds using the plurality of confidence scores. Managing confidence data can include classifying unclassified confidence scores of the third set into one of the plurality of confidence buckets using the fifth set of the plurality of thresholds.

Abstract: Managing confidence data in a question-answering environment is disclosed. Managing confidence data can include sorting, based on a set of answer categories for a subject matter, a first set of a plurality of answers into a first answer category. The first set can correspond to at least one of a third set of a plurality of confidence scores and the second set can correspond to at least one of a fourth set of the plurality of confidence scores. Managing confidence data can include classifying confidence scores of the third set into one of a plurality of confidence buckets using a first threshold and determining a fifth set of a plurality of thresholds using the plurality of confidence scores. Managing confidence data can include classifying unclassified confidence scores of the third set into one of the plurality of confidence buckets using the fifth set of the plurality of thresholds.