Abstract: Embodiments presented herein disclose techniques for transforming input documents having disparate formats into a normalized format (e.g., Atom, RSS, HTML, customized XML, etc.). According to one embodiment, a plurality of fields is identified in an input document that has a given format. Each field includes a descriptor and text content associated with the descriptor. For each field, semantic properties are evaluated for the descriptor and text content against a plurality of mapping rules to determine whether the field is consistent with one of a plurality of fields of a target format. Each mapping rule specifies characteristics associated with one of the fields in the target format. Once so determined, a mapping from the first field to the second field is defined.

Abstract: Embodiments presented herein disclose techniques for transforming input documents having disparate formats into a normalized format (e.g., Atom, RSS, HTML, customized XML, etc.). According to one embodiment, a plurality of fields is identified in an input document that has a given format. Each field includes a descriptor and text content associated with the descriptor. For each field, semantic properties are evaluated for the descriptor and text content against a plurality of mapping rules to determine whether the field is consistent with one of a plurality of fields of a target format. Each mapping rule specifies characteristics associated with one of the fields in the target format. Once so determined, a mapping from the first field to the second field is defined.

Abstract: A patient's medical history is built by applying natural language processing to multiple patient records and identifying medical concepts with associated dates for each document. The documents are grouped into clusters based on the dates, and a primary concept is determined for each cluster by performing an analysis which assigns confidence values to the documents and selects the medical concept in the document having the highest confidence value as the primary concept. Primary concepts from respective document clusters are combined to generate a combined history. If the combined history is not feasible due to a conflict between primary concepts, the documents can be re-grouped into different clusters, and the analysis repeated. The invention can further identify an inter-concept conflict among the primary concepts involving at least two different concept types, then receive guidelines pertaining to relationships between the different concept types, and resolve the conflict by applying the relationships.

Abstract: An approach is provided in which a knowledge manager analyzes multiple document phrases using a natural language processing model and generates multiple interpretations based upon the analysis. The knowledge manager identifies misinterpretation patterns by comparing the multiple interpretations with multiple corrections that include corrections to the multiple interpretations. In turn, the knowledge manager generates interpretation rules based upon the identified patterns and applies the interpretation rules to the natural language processing model.

Abstract: Mechanisms are provided, in a Question and Answer (QA) system comprising a processor and a memory, for debugging code. An input question identifying an error during execution of code is processed by the QA system using a corpus corresponding to a software product associated with the code, thereby generating a first candidate answer set. The QA system processes the input question using a code change record repository identifying changes to the code performed over time to generate a second candidate answer set. The QA system generates a final answer to the input question based on the first and second candidate answer sets and outputs the final answer to the input question. The final answer to the input question identifies at least one of a source, in the code, of the error or a solution to resolving the error.

Abstract: An approach is provided in which a knowledge manager analyzes multiple document phrases using a natural language processing model and generates multiple interpretations based upon the analysis. The knowledge manager identifies misinterpretation patterns by comparing the multiple interpretations with multiple corrections that include corrections to the multiple interpretations. In turn, the knowledge manager generates interpretation rules based upon the identified patterns and applies the interpretation rules to the natural language processing model.

Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer (QA) system, for effectively ingesting data for answering questions in the QA system. A received input question having a set of question characteristics is parsed, which are compared to question characteristics associated with a set of previous questions. Responsive to the set of question characteristics matching the question characteristics associated with one or more previous questions above a related-question predetermined threshold, identification is made as to whether answers to the one or more previous questions were obtained from static information sources or real-time information sources.

Abstract: An approach is provided in which a knowledge manager analyzes multiple document phrases using a natural language processing model and generates multiple interpretations based upon the analysis. The knowledge manager identifies misinterpretation patterns by comparing the multiple interpretations with multiple corrections that include corrections to the multiple interpretations. In turn, the knowledge manager generates interpretation rules based upon the identified patterns and applies the interpretation rules to the natural language processing model.

Abstract: An approach is provided in which a knowledge manager analyzes multiple document phrases using a natural language processing model and generates multiple interpretations based upon the analysis. The knowledge manager identifies misinterpretation patterns by comparing the multiple interpretations with multiple corrections that include corrections to the multiple interpretations. In turn, the knowledge manager generates interpretation rules based upon the identified patterns and applies the interpretation rules to the natural language processing model.

Abstract: Embodiments presented herein disclose techniques for transforming input documents having disparate formats into a normalized format (e.g., Atom, RSS, HTML, customized XML, etc.). According to one embodiment, a plurality of fields is identified in an input document that has a given format. Each field includes a descriptor and text content associated with the descriptor. For each field, semantic properties are evaluated for the descriptor and text content against a plurality of mapping rules to determine whether the field is consistent with one of a plurality of fields of a target format. Each mapping rule specifies characteristics associated with one of the fields in the target format. Once so determined, a mapping from the first field to the second field is defined.

Abstract: Embodiments presented herein disclose techniques for transforming input documents having disparate formats into a normalized format (e.g., Atom, RSS, HTML, customized XML, etc.). According to one embodiment, a plurality of fields is identified in an input document that has a given format. Each field includes a descriptor and text content associated with the descriptor. For each field, semantic properties are evaluated for the descriptor and text content against a plurality of mapping rules to determine whether the field is consistent with one of a plurality of fields of a target format. Each mapping rule specifies characteristics associated with one of the fields in the target format. Once so determined, a mapping from the first field to the second field is defined.

Abstract: An approach is provided in which an information handling system extracts treatment segments from documents corresponding to a patient and uses cognitive analysis to identify common treatment properties of a subset of the treatment segments. The information handling system combines the subset of treatment segments into a treatment aggregation that corresponds to a treatment history of the patient. In turn, the information handling system ingests the treatment aggregation into a domain for subsequent processing.

Abstract: An approach is provided in which a knowledge manager selects patient data measurements corresponding to a patient that is on a current treatment plan. The patient data measurements correspond to different test results of the patient. The knowledge manager analyzes the patient data measurements against guideline threshold compilations that include multiple guideline thresholds. In turn, the knowledge manager determines a patient response of the patient and chronologically maps the patient response to the treatment plan.

Abstract: Mechanisms are provided, in a Question and Answer (QA) system comprising a processor and a memory, for debugging code. An input question identifying an error during execution of code is processed by the QA system using a corpus corresponding to a software product associated with the code, thereby generating a first candidate answer set. The QA system processes the input question using a code change record repository identifying changes to the code performed over time to generate a second candidate answer set. The QA system generates a final answer to the input question based on the first and second candidate answer sets and outputs the final answer to the input question. The final answer to the input question identifies at least one of a source, in the code, of the error or a solution to resolving the error.

Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer (QA) system, for effectively ingesting data for answering questions in the QA system. A received input question having a set of question characteristics is parsed, which are compared to question characteristics associated with a set of previous questions. Responsive to the set of question characteristics matching the question characteristics associated with one or more previous questions above a related-question predetermined threshold, identification is made as to whether answers to the one or more previous questions were obtained from static information sources or real-time information sources.