International Business Machines Corporation

Kristin A Witherspoon

Daniel M Jamrog

Jason D LaVoie

Nicholas W Orrick

Corville O Allen

Donna Karen Byron

Elie Feirouz

Alexander Pikovsky

Aleksandr Evgenyevich Petrov

Jeffrey R Pratt

Kavita Patil

Edward T Winchester

Romina M J Jose

Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Method to allow for question and answer system to dynamically return different responses based on roles

An approach is provided to adjust time dependent terminology in a question and answering (QA) system. The approach ingests a set of documents to produce a corpus utilized by the QA system. A base time is established and the approach acquires a temporally accurate lexicon of terms that correspond to the base time. A corpus of the QA system is updated according to the lexicon. The QA system answers a question according to the updated corpus.

Adjusting time dependent terminology in a question and answer system

A method, system and computer-usable medium are disclosed for enhancing a classification system to include an automatic classification validation system. The automatic classification validation system takes the classification results and automatically validates them for correctness. More specifically, the automatic classification validation system analyzes the data objects in the categories and, if any outliers are identified, then determines a context of the data object from a plurality of records contained within a certain category to determine the context. The classification validation system then uses the context of the data object to validate the classification.

System and method for automatically validating classified data objects

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 weighting search criteria based on similarities to an ingested corpus in the QA system. A set of question characteristics found in a received input question are compared to a set of data characteristics respectively describing data in each corpus of a corpora. For each question characteristic in the set of found question characteristics, a first weight is assigned to the corpus within which data associated with the data characteristic resides in response to the question characteristic being more related to a data characteristic; otherwise a second weight is assigned, where the first weight is greater than the second weight. A selective search is then performed for an answer to the received input question in one or more corpora with a higher weighting.

Weighting search criteria based on similarities to an ingested corpus in a question and answer (QA) system

A question-answering (QA) system first receives input questions. Each question is then assigned to a first question category of a plurality of question categories. The QA system then identifies a set of candidate answers to each question using a core information source. A set of confidence scores, including a confidence score for each candidate answer, is then calculated. The QA system then determines that the first set of confidence scores fails to satisfy confidence criteria. In response to this determination, an updated information source is ingested.

Handling information source ingestion in a question answering system

An approach is provided for updating corpora in a Question and Answer (QA) system. Ingestion of a first set of sources into a first corpus and a second set of sources into a second corpus with the second set of sources including updates to the first set of sources. A question is received. The system identifies candidate answers to the question using the sources included in the corpuses. Each candidate answer has a weighting. The system determines whether the first and second corpuses have an overlapping source from which two candidate answers were identified. If an overlapping source is found, the candidate answer from the overlapping source in the first corpus is assigned a lower weighting than the candidate answer from the second corpus. Likely answers are selected from the candidate answers based on the weighting and returned to the requestor.

Realtime ingestion via multi-corpus knowledge base with weighting

An approach is provided for utilizing unstructured corpora in a Question and Answer (QA) system. A question is received at the QA system. A private corpora is generated with the private corpora being associated with the user. The private corpora is generated from private data stores associated with the user as well as private data stores associated with other users. Access to the other user's private data sources is provided to the user by the other users. The system retrieves data responsive to the question from the private corpora. The responsive data is ranked based on its relevance to the question. Likely answers are identified based on the ranked responsive data and the likely answers are provided back to the user.

Collection and storage of a personalized, searchable, unstructured corpora

Mechanisms for ingesting a document from a corpus of documents for use by a Question and Answer (QA) system are provided. The mechanisms receive a document from a corpus of documents and generate one or more titles for the document based on an analysis of content of the document. The mechanisms generate score values for the titles based on a measure of a degree to which the titles represent the content of the document. The mechanisms store the score values in association with the titles as document metadata associated with the document and output the document and document metadata to the QA system. The QA system utilizes the document metadata and document to generate a candidate answer to an input question.

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Somerville, MA, United States of America

Kristin A Witherspoon