Abstract: A mechanism is provided, in a question answering (QA) system, for performing persona-based question answering is provided. An identification of a requested persona is received from a user along with a natural language question input specifying an input question to be answered by the QA system. Responsive to receiving the requested persona, components of the QA system are customized to answer questions from a viewpoint of the requested persona. An answer to the input question is generated from the viewpoint of the requested persona based on the customization of the components of the QA system. The answer to the input question is output in a form representative of the requested persona.

Abstract: Embodiments of the present invention disclose a method for processing tabular data. In various embodiments, an electronic document is received through a network, along with associated metadata. A plurality of table markers, or tabular data markers, are identified, in response to analyzing the received electronic document for said markers. References and citations associated with the plurality of tabular data markers are identified. A graphical representation of the relationship between identified tabular data markers and the identified references is generated. A uniqueness score is calculated, based on the generated graph and an ingestion plan is generated for the received electronic documents based on the calculated uniqueness score value.

Abstract: A mechanism is provided, in a question answering (QA) system, for performing persona-based question answering is provided. An identification of a requested persona is received from a user along with a natural language question input specifying an input question to be answered by the QA system. Responsive to receiving the requested persona, components of the QA system are customized to answer questions from a viewpoint of the requested persona. An answer to the input question is generated from the viewpoint of the requested persona based on the customization of the components of the QA system. The answer to the input question is output in a form representative of the requested persona.

Abstract: Mechanisms are provided to implement a cognitive system collaboration identification and recommendation system (CSCIRS). The CSCIRS stores, in a cognitive system database, entries corresponding to a plurality of cognitive system instances. Each entry identifies operational characteristics of a corresponding cognitive system instance. The CSCIRS receives, from a requestor, a request to identify a potential collaborative cognitive system instance and identifies, based on the request and the cognitive system database, a candidate collaborative cognitive system instance. The CSCIRS generates a collaboration recommendation based on the identification and outputs an output corresponding to the collaboration recommendation.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for a computer implemented method for processing tabular data. In various embodiments, an electronic document is received through a network, along with associated metadata. A plurality of table markers, or tabular data markers, are identified, in response to analyzing the received electronic document for said markers. References and citations associated with the plurality of tabular data markers are identified. A graphical representation of the relationship between identified tabular data markers and the identified references is generated. A uniqueness score is calculated, based on the generated graph and an ingestion plan is generated for the received electronic documents based on the calculated uniqueness score value.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for a computer implemented method for processing tabular data. In various embodiments, an electronic document is received through a network, along with associated metadata. A plurality of table markers, or tabular data markers, are identified, in response to analyzing the received electronic document for said markers. References and citations associated with the plurality of tabular data markers are identified. A graphical representation of the relationship between identified tabular data markers and the identified references is generated. A uniqueness score is calculated, based on the generated graph and an ingestion plan is generated for the received electronic documents based on the calculated uniqueness score value.

Abstract: Embodiments of the present invention disclose a method for processing tabular data. In various embodiments, an electronic document is received through a network, along with associated metadata. A plurality of table markers, or tabular data markers, are identified, in response to analyzing the received electronic document for said markers. References and citations associated with the plurality of tabular data markers are identified. A graphical representation of the relationship between identified tabular data markers and the identified references is generated. A uniqueness score is calculated, based on the generated graph and an ingestion plan is generated for the received electronic documents based on the calculated uniqueness score value.

Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values. A set of temporal characteristics is identified of a set of initial candidate answers. For each initial candidate answer in the set of initial candidate answers: a distance value is generated for each of the set of temporal characteristics of the set of initial candidate answers, a multiplier value is determined with which to weight an initial confidence score associated with the initial candidate answer using the distance value; a sentiment value is determined of the initial candidate answer, and a final weight value is determined using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer. A set of temporally refined candidate answers is then provided using the determined final weight values.

Abstract: A system, and computer program product for subject-matter analysis of tabular data are provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: A method for discovering relationships in tabular data is provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.

Abstract: A system, and computer program product for discovering relationships in tabular data are provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.

Abstract: A method, system, and computer program product for subject-matter analysis of tabular data are provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for providing confidence rankings based on temporal semantics. Responsive to receiving an input question, a set of candidate answers is identified from a knowledge domain based on a correlation between an identified one or more predicates and an identified one or more arguments to the knowledge domain. A confidence score is associated with each of the candidate answers and each confidence score associated with each candidate answer is refined based on a set of temporal characteristics identified in the input question. A set of temporally refined candidate answers is then provided to the user.

Abstract: An approach is provided to receive audible speech and convert the received speech to text while the audible speech is being delivered to a user. An annotation candidate is identified in the text and an annotation reference relating to the identified annotation candidate is retrieved and presented to the user.

Abstract: Mechanisms are provided for performing an analysis of content based on a flow of property between entities. The mechanisms analyze a corpus of unstructured documents to identify one or more asset transfer flow relationships between entities. The mechanisms generate an asset transfer flow model defining a flow of an asset between entities based on the one or more asset transfer flow relationships between entities. The mechanisms input the asset transfer flow model into an analysis engine for use in analyzing content. The mechanisms analyze the content using the asset transfer flow model to generate results of the analysis and output the results of the analysis based on the asset transfer flow model.

Abstract: An approach is provided for an information handling system that includes a processor and a memory to generate a table of contents pertaining to a document. The approach semantically analyzes the document to identify semantic relationships of proximate elements of the document. A number of candidate headings corresponding to a semantically related section of the document are identified and each of the candidate headings are scored. Based on the scores of each of the candidate headings, a section heading for the semantically related section of the document is selected. The selected heading is then included in the table of contents for the section of the document. The process of identifying candidate headings, scoring candidates, and selecting the section heading is repeated for other semantically related sections of the document.

Abstract: A mechanism is provided in a data processing system for rating difficulty of a question. The mechanism receives an input question and generates one or more candidate answers from a corpus of knowledge using a pipeline of software engines. The pipeline of software engines generates a plurality of features extracted from the question, the one or more candidate answers, or the corpus of knowledge. The mechanism then generates a question difficulty score based on the plurality of features using a machine learning model. The machine learning model maps features to assigned weights for scaling the difficulty score.

Abstract: Mechanisms for training a Question and Answer (QA) system are provided. The QA system receives a training question for processing by the QA system and processes the training question to generate an answer to the training question, from a portion of content. The QA system identifies a repeatable pattern of content present in the portion of content in association with the answer to the training question. The QA system applies the repeatable pattern of content to other portions of content to generate at least one additional training question and at least one additional entry in a ground truth data structure to thereby expand a set of training questions and expand the ground truth data structure. The QA system is then trained using the expanded set of training questions and expanded ground truth data structure.

Abstract: A mechanism is provided, in a question answering (QA) system, for performing persona-based question answering is provided. An identification of a requested persona is received from a user along with a natural language question input specifying an input question to be answered by the QA system. Responsive to receiving the requested persona, components of the QA system are customized to answer questions from a viewpoint of the requested persona. An answer to the input question is generated from the viewpoint of the requested persona based on the customization of the components of the QA system. The answer to the input question is output in a form representative of the requested persona.