Abstract: Embodiments are directed to an entity extraction and filtering method that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering method operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.

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: Embodiments are directed to interaction with an open-domain question and answer system to seek answers to broad and general questions by providing templates and words or phrases to fill slots in the templates that specify alternative specific questions, the answer to any of which may serve the broader purpose. Responses to all of the questions in a batch are considered as candidates, with the strongest general answers being returned. The approach, according to embodiments herein, addresses the need for responses to broad questions in which the user is seeking any response to a known pattern. The user is able to articulate the question as a template that can be instantiated in many forms, and the user may specify how strongly the concrete answers indicate an answer to the underlying general question.

Abstract: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

Abstract: Embodiments are directed to interaction with an open-domain question and answer system by recognizing questions that are highly broad or abstract, and generating and processing a batch of questions expressing alternate, concrete instances of the more general, abstract question. Responses to all of the questions in the batch are considered as candidates, and the strongest general answers are returned. A weighted, ranked answer set, based on weighting individual concrete questions and scaling the answers proportional to the weight of the questions, is provided to the user. The approach, according to embodiments herein, addresses the need for responses to broad questions in which a response to any of a set of more concrete question instances may serve to answer the question.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

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: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

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: 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 embodiment of the invention may include a method, computer program product and system for generating follow-up questions based on machine learning utilizing a computing device. The embodiment may include receiving an input question from a user. The embodiment may include parsing the received input question to extract input question components. Parsing utilizes natural language processing techniques. The embodiment may include executing trained question component models to predict follow-up question components. The extracted input question components are utilized as inputs to the trained question component models. The embodiment may include combining the predicted follow-up question components to generate one or more follow-up questions. The embodiment may include returning the one or more follow-up questions to the user.

Abstract: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

Abstract: The present invention may include an embodiment to improve the performance (both response time and quality of answers) of a knowledge based service operating on a master catalog of data by dynamically building a narrowed, focused, and reduced corpus of data over which the knowledge based service operates. The embodiment may identify a corpus catalog for a knowledge base service, where the knowledge base service includes one or more documents. Then the embodiment may determine one or more subjects based on profile preferences of a user and determining the one or more documents corresponding to the determined one or more subjects based on determining the one or more subjects were updated. The embodiment may stage the determined one or more documents in a master corpus, where the master corpus is a subset of the corpus catalog and upload the master corpus to the knowledge base service.

Abstract: In an approach to watching hypotheses in a deep question answering system, one or more processors receive a question from a user and generate a first result set based on the question. One or more processors receive a request from the user to watch one or more hypothesis answers in the first result set. One or more processors generate a second result set based on the question, where the second result set is generated at a later time than the first result set. One or more processors further determine a similarity score between a hypothesis answer in the second set of one or more hypothesis answers and the watched one or more hypothesis answers and, responsive to determining that the similarity score is below a predetermined threshold, one or more processors send a contradiction alert to the user indicating a potential alternative hypothesis.

Abstract: Embodiments can provide a computer implemented method for harvesting training data for a training set for use by a system capable of answering questions, the system comprising a processor and a memory comprising instructions executed by the processor, the method comprising receiving, from a user, an input question; processing the input question and returning, to the user, a result set comprising one or more ranked hypotheses and one or more ranked evidence passages corresponding to the one or more ranked hypotheses; receiving, from the user, an indication that one of the one or more ranked hypotheses is to be designated a watched hypothesis; adding the input question and the watched hypothesis to a to-be-vetted question/answer (QA) pair set comprising one or more to-be-vetted QA pairs; vetting each of the one or more to-be-vetted QA pairs in the to-be-vetted QA pair set through a first-pass automatic vetting procedure; if a vetted QA pair passes the first-pass automatic vetting procedure, adding the vetted QA

Abstract: A computer-implemented method comprising: receiving, by a computing device, biometrics data of a user via a user device as part of a request to access a secure device; applying, by the computing device, a non-invertible function to the biometrics data to scramble the biometrics data; determining, by the computing device, whether the scrambled biometrics data matches a pre-registered version of the scrambled biometrics data; and providing, by the computing device, an authentication message to the secure device requesting authentication of the user based on determining that the scrambled biometrics data matches the pre-registered version of the scrambled biometrics data, wherein the providing the authentication message provides a user of the user device with access to the secure device.

Abstract: Embodiments are directed to an entity extraction and filtering system that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering system operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.

Abstract: Embodiments are directed to an entity extraction and filtering method that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering method operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.

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.