Abstract: 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.

Abstract: 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.

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 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.

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 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An approach is provided for mining threaded online discussions. In the approach, performed by an information handling system, a natural language processing (NLP) analysis is performed on threaded discussions pertaining to a given topic. The analysis is performed across multiple web sites with each of the web sites including one or more threaded discussions. The analysis results in harvested discussions pertaining to the topic. The harvested discussions are correlated and a question is identified from the harvested discussions. A set of candidate answers is also identified from the harvested discussions, with one of the candidate answers being selected as the most likely answer to the identified question.

Abstract: An approach is provided for mining threaded online discussions. In the approach, performed by an information handling system, a natural language processing (NLP) analysis is performed on threaded discussions pertaining to a given topic. The analysis is performed across multiple web sites with each of the web sites including one or more threaded discussions. The analysis results in harvested discussions pertaining to the topic. The harvested discussions are correlated and a question is identified from the harvested discussions. A set of candidate answers is also identified from the harvested discussions, with one of the candidate answers being selected as the most likely answer to the identified question.

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 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.

Abstract: According to one embodiment of the present disclosure, an approach is provided in which a processor receives a media stream that includes media content. The processor selects a media stream segment included in the media stream, and generates annotated data based upon a portion of the media content included in the selected media stream segment. The processor, in turn, compares the annotated data with obfuscation preferences that correspond to prohibited content, and modifies the media stream segment in response to the comparison.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system, a method, and a computer program product of searching a corpus with an unstructured query in a Question and Answering (QA) system are disclosed. The system, the method, and the computer program product include analyzing structural information of an input question. The analyzing may occur in response to parsing the input question. The analyzing may select a first portion of the input question as a first component. The system, the method, and the computer program product include weighting the first component with a first weight. The weighting may be used in a query. The system, the method, and the computer program product include submitting the query to the QA system. The query may include the first component with the first weight.

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 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.

Abstract: A system, a method, and a computer program product of searching a corpus with an unstructured query in a Question and Answering (QA) system are disclosed. The system, the method, and the computer program product include analyzing structural information of an input question. The analyzing may occur in response to parsing the input question. The analyzing may select a first portion of the input question as a first component. The system, the method, and the computer program product include weighting the first component with a first weight. The weighting may be used in a query. The system, the method, and the computer program product include submitting the query to the QA system. The query may include the first component with the first weight.