Abstract: Embodiments can provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement an enhanced corpus management system, the method comprising: identifying one or more functional domain categories; ingesting one or more incoming documents to form an open-domain corpus; for each functional domain category, identifying one or more representative documents to establish a seed sub-corpus; calculating a degree of fit score between each of the one or more incoming documents and the one or more established functional domain category seed sub-corpora; and assigning one or more of the incoming documents to one or more of the functional domain categories based upon the degree of fit score to create an enhanced corpus.

Abstract: An approach is provided for ranking candidate answers to a natural language question. First contextual information about a user of a mobile device is identified. A prioritization of definitions of terms is determined. Based on the prioritization, a lexicon of the terms is generated. Using mobile-based time series manipulation and pattern recognition and based on historical usage of the mobile device, a location of the user, an environment of the user, and a bodily function of the user, second contextual information is forecasted. Based on a word sense disambiguation of the terms in the lexicon and an adjustment of the prioritization, candidate answers are modified and then ranked. The highest ranked candidate answer is more likely to be a correct answer to the natural language question than the other candidate answers.

Abstract: A candidate document is received, for example, by a document filter. A determination is made based on the content of the candidate document, whether the candidate document is relevant to a document corpus. A determination is made based on the content of the candidate document, whether the candidate document is novel with respect to the document corpus. In response to determining that the candidate document is relevant to the document corpus and novel with respect to the document corpus, the candidate document is added to the document corpus to make at least a portion of the content of the candidate document available for a response to a search query.

Abstract: Batch interaction with a computerized question answering system can produce an answer that more closely relates to a user's information need. A batch of questions can be generated interactively, and provides a context for a first question received from a user. The batch of questions includes or more additional questions which have terms with a nonsynonymous semantic relation to a first term in the first question. A question answering system can process the batch of questions to determine candidate answers. An answer to the first question can be determined based, at least in part, on a combined ranking of the candidate answers.

Abstract: An approach is provided for ranking candidate answers to a natural language question. First contextual information about a user of a mobile device is identified. A prioritization of definitions of terms is determined. Based on the prioritization, a lexicon of the terms is generated. Using mobile-based time series manipulation and pattern recognition and based on historical usage of the mobile device, a location of the user, an environment of the user, and a bodily function of the user, second contextual information is forecasted. Based on a word sense disambiguation of the terms in the lexicon and an adjustment of the prioritization, candidate answers are modified and then ranked. The highest ranked candidate answer is more likely to be a correct answer to the natural language question than the other candidate answers.

Abstract: Methods, computer program products and systems for generating at least one factual question from a set of seed questions and answer pairs. One method includes: obtaining at least one seed question and answer pair from the set of seed question and answer pairs; extracting a set of features associated with the at least one seed question and answer pair using at least one common analysis system (CAS) in a set of CASs and a specific knowledge base; generating a set of candidate questions from the extracted set of features using a logistic regression algorithm and the specific knowledge base; and ranking each candidate question relative to a remainder of candidate questions in the set of candidate questions based on the extracted set of features and the at least one seed question and answer pair.

Abstract: An approach is provided for ranking candidate answers to a natural language question. Candidate answers to a natural language question received from a mobile device are generated. First contextual information about a user of the mobile device is identified. A prioritization of definitions of terms is determined. Based on the prioritization, a lexicon of the terms is generated. Using mobile-based time series manipulation and pattern recognition and based on historical usage of the mobile device, a location of the user, an environment of the user, and a bodily function of the user, second contextual information is forecasted. Based on a word sense disambiguation of the terms in the lexicon and an adjustment of the prioritization, the candidate answers are modified and then ranked. The highest ranked candidate answer is more likely to be a correct answer to the natural language question than the other candidate answers.

Abstract: Methods, computer program products and systems for generating at least one factual question from a set of seed questions and answer pairs. One method includes: obtaining at least one seed question and answer pair from the set of seed question and answer pairs; extracting a set of features associated with the at least one seed question and answer pair using at least one common analysis system (CAS) in a set of CASs and a specific knowledge base; generating a set of candidate questions from the extracted set of features using a logistic regression algorithm and the specific knowledge base, wherein each candidate question includes an expansion of each of the extracted set of features; and ranking each candidate question relative to a remainder of candidate questions in the set of candidate questions based on the extracted set of features and the at least one seed question and answer pair.

Abstract: An approach is provided for ranking candidate answers to a natural language question. Candidate answers to a natural language question received from a mobile device are generated. First contextual information about a user of the mobile device is identified. A prioritization of definitions of terms is determined. Based on the prioritization, a lexicon of the terms is generated. Using mobile-based time series manipulation and pattern recognition and based on historical usage of the mobile device, a location of the user, an environment of the user, and a bodily function of the user, second contextual information is forecasted. Based on a word sense disambiguation of the terms in the lexicon and an adjustment of the prioritization, the candidate answers are modified and then ranked. The highest ranked candidate answer is more likely to be a correct answer to the natural language question than the other candidate answers.

Abstract: An approach is provided for ranking candidate answers to a natural language question. A natural language question is received from a user of a mobile device. Candidate answers to the received natural language question are generated. A lexicon is generated based on contextual information of the user determined by the mobile device. Contextual information of the user is forecasted based on usage of the mobile device. Based in part on the lexicon and the forecasted contextual information, the candidate answers to the natural language question are ranked.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods. In some embodiments, a system includes a method of providing a confidence-estimation-based inference, the method includes receiving a query concerning a patient from a user, accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient, querying the user, using a conversational interface, for a second component regarding the patient, receiving the second component regarding the patient in response to the query, calculating a first probability density function using the first component, and a second probability density function using the second component, combining the first and second probability density functions using a Gaussian mixture model, calculating at least one conditional probability table using the Gaussian mixture model and providing the confidence-estimation-based inference based on the at least one conditional probability table.

Abstract: An approach is provided for ranking candidate answers to a natural language question. A natural language question is received from a user of a mobile device. Candidate answers to the received natural language question are generated. A lexicon is generated based on contextual information of the user determined by the mobile device. Contextual information of the user is forecasted based on usage of the mobile device. Based in part on the lexicon and the forecasted contextual information, the candidate answers to the natural language question are ranked.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods.

Abstract: Methods, computer program products and systems for generating at least one factual question from a set of seed questions and answer pairs. One method includes: obtaining at least one seed question and answer pair from the set of seed question and answer pairs; extracting a set of features associated with the at least one seed question and answer pair using at least one common analysis system (CAS) in a set of CASs and a specific knowledge base; generating a set of candidate questions from the extracted set of features using a logistic regression algorithm and the specific knowledge base; and ranking each candidate question relative to a remainder of candidate questions in the set of candidate questions based on the extracted set of features and the at least one seed question and answer pair.

Abstract: Methods, computer program products and systems for generating at least one factual question from a set of seed questions and answer pairs. One method includes: obtaining at least one seed question and answer pair from the set of seed question and answer pairs; extracting a set of features associated with the at least one seed question and answer pair using at least one common analysis system (CAS) in a set of CASs and a specific knowledge base; generating a set of candidate questions from the extracted set of features using a logistic regression algorithm and the specific knowledge base, wherein each candidate question includes an expansion of each of the extracted set of features; and ranking each candidate question relative to a remainder of candidate questions in the set of candidate questions based on the extracted set of features and the at least one seed question and answer pair.