Abstract: A mechanism is provided in a data processing system for determining source authority for an answer to a question. The mechanism receives an input question from a user interface and determines a set of answers to the input question from a corpus of information. The corpus of information comprises a plurality of sources of information. For a given answer in the set of answers, the mechanism identifies a given source of a supporting passage. The mechanism determines an authority score of the given source for the input question. The mechanism presents the set of answers to the user interface based on the authority score for the given source.

Abstract: Context data is determined for a web page. The context data includes textual data that describes subject matter displayed on the web page. A client query is retrieved from a client-retrieved instance of the web page. An identifier associated with the web page capable of distinguishing the web page from other web pages is determined. In response to receiving the client query, a plurality of queries are retrieved from a database. Whether one or more of the retrieved queries correlate the determined web page context and the received client query is determined. A set of one or more queries from the plurality of queries is selected based on the selected set of queries each having been determined to correlate the web page context data and the client query. The selected set of the plurality of the queries is sent to the client-retrieved instance of the web page.

Abstract: Mechanisms are provided for performing an operation based on an identification of similar lines of questioning by input question sources. Question information identifying extracted features of an input question and a first source of the input question is obtained. A clustering operation is performed to cluster the input question with one or more other questions of a cluster based on a similarity of the extracted features of the input question to features of the one or more other questions. An operation is performed based on results of the clustering of the input question with the one or more other questions.

Abstract: An approach is provided for evaluating subject matter experts (SMEs) in a question and answering (QA) system. In the approach, a number of responses are received at the QA system with each of the responses being a response to a common question and each of the responses being received from a SME. One of the responses is selected with the selected response being from one of the SMEs that is being evaluated. The approach evaluates the selected response by comparing the selected response to the responses received from the other SMEs. Based on the evaluation, the approach updates a SME confidence score that corresponds to the selected SME.

Abstract: Mechanisms for generating an answer to an input question are provided. The mechanisms receive an input question and route the input question to a plurality of Question and Answer (QA) system pipelines. The mechanisms receive results of processing the input question from each QA system pipeline in the plurality of QA system pipelines. The results comprise one or more candidate answers to the input question and associated confidence scores. The mechanisms adjust, for each QA system pipeline, the confidence scores of the one or more candidate answers associated with the QA system pipeline based on one or more weighting factors. In addition, the mechanisms generate the answer to the input question based on the adjusted confidence scores of the one or more candidate answers for each QA system pipeline.

Abstract: Context data is determined for a web page. The context data includes textual data that describes subject matter displayed on the web page. A client query is retrieved from a client-retrieved instance of the web page. An identifier associated with the web page capable of distinguishing the web page from other web pages is determined. In response to receiving the client query, a plurality of queries are retrieved from a database. Whether one or more of the retrieved queries correlate the determined web page context and the received client query is determined. A set of one or more queries from the plurality of queries is selected based on the selected set of queries each having been determined to correlate the web page context data and the client query. The selected set of the plurality of the queries is sent to the client-retrieved instance of the web page.

Abstract: Mechanisms are provided for performing load balancing of question processing in a Question and Answer (QA) system, implemented by the data processing system, having a plurality of QA system pipelines. The mechanisms receive an input question for processing by the QA system and determine a predicted question difficulty of the input question. The mechanisms select a QA system pipeline from the plurality of QA system pipelines based on the predicted question difficulty and route the input question to the selected QA system pipeline for processing. In addition, the mechanisms process the input question with the selected QA system pipeline to generate an answer for the input question.

Abstract: Mechanisms are provided for managing a corpus of content. A question is processed by a Question Answering (QA) system to generate an answer to the question and a supporting evidence passage. A corpus value metric is calculated for the supporting evidence passage based on a determined number of times the supporting evidence passage is used to generate a high ranking answer to questions submitted to the QA system. A first corpus management operation is performed on the supporting evidence passage in response to determining that the corpus value metric meets or exceeds a first threshold, the first corpus management operation increasing a relative importance of the supporting evidence passage within the corpus. A second corpus management operation on the supporting evidence passage is performed in response to determining that the corpus value metric meets or falls below a second threshold, the second corpus management operation decreasing the passage's relative importance.

Abstract: Mechanisms are provided, in a Question and Answer (QA) system, for identifying a related previously processed question. A first question is processed by the QA system to generate an answer to the first question and a supporting evidence passage that supports the answer to the first question being a correct answer to the first question. The QA system performs a lookup operation in a question repository based on an identifier of the supporting evidence passage to identify an entry corresponding to a previously processed question, different than the first question, that previously had an answer generated based on the supporting evidence passage. The QA system returns the previously processed question and the answer to the first question to a submitter of the first question.

Abstract: Mechanisms are provided for managing a corpus of content. A question is processed by a Question Answering (QA) system to generate an answer to the question and a supporting evidence passage. A corpus value metric is calculated for the supporting evidence passage based on a determined number of times the supporting evidence passage is used to generate a high ranking answer to questions submitted to the QA system. A first corpus management operation is performed on the supporting evidence passage in response to determining that the corpus value metric meets or exceeds a first threshold, the first corpus management operation increasing a relative importance of the supporting evidence passage within the corpus. A second corpus management operation on the supporting evidence passage is performed in response to determining that the corpus value metric meets or falls below a second threshold, the second corpus management operation decreasing the passage's relative importance.

Abstract: An approach is provided dynamically prioritizing question requests based on extracted question data. In the approach, performed by an information handling system, a number of question requests to a question and answering (QA) system are received from a computer network, and a plurality of question priority parameters are identified, including one or more question topics and a plurality question context parameters, by performing natural language processing (NLP) analysis of each question request. The approach determines a target priority value for each question request based on the plurality of question priority parameters identified for said question request. By evaluating the target priority values for the plurality of question requests, processing of the question requests is prioritized, such as by applying an artificial intelligence (AI) learned models and rule-based logic at the information handling system to evaluate the target priority values for the plurality of question requests.

Abstract: An approach is provided dynamically prioritizing question requests based on extracted question data. In the approach, performed by an information handling system, a number of question requests to a question and answering (QA) system are received from a computer network, and a plurality of question priority parameters are identified, including one or more question topics and a plurality question context parameters, by performing natural language processing (NLP) analysis of each question request. The approach determines a target priority value for each question request based on the plurality of question priority parameters identified for said question request. By evaluating the target priority values for the plurality of question requests, processing of the question requests is prioritized, such as by applying an artificial intelligence (AI) learned models and rule-based logic at the information handling system to evaluate the target priority values for the plurality of question requests.

Abstract: Mechanisms are provided for performing load balancing of question processing in a Question and Answer (QA) system, implemented by the data processing system, having a plurality of QA system pipelines. The mechanisms receive an input question for processing by the QA system and determine a predicted question difficulty of the input question. The mechanisms select a QA system pipeline from the plurality of QA system pipelines based on the predicted question difficulty and route the input question to the selected QA system pipeline for processing. In addition, the mechanisms process the input question with the selected QA system pipeline to generate an answer for the input question.

Abstract: Mechanisms are provided in a data processing system for utilizing algorithms based on categories in a question answering system. The mechanisms capture a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to questions in respective question categories in a question answering system. The mechanisms determine sets of algorithms to use for respective question categories according to efficiency and correctness analysis. The mechanisms determine a question category of a given input question and execute a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question.

Abstract: Mechanisms for selecting a pipeline of a question and answer (QA) system to process an input question are provided. An input question is received and analyzed to identify at least one feature of the input question. Clustering of the input question, with one or more previously generated clusters of questions, is performed based on the at least one feature of the input question. Based on results of the clustering, a matching cluster, of the one or more previously generated clusters, is identified with which the input question is associated. A QA system pipeline associated with the matching cluster is identified and the input question is processed using the identified QA system pipeline to generate one or more candidate answers for the input question. Each cluster in the one or more previously generated clusters has an associated QA system pipeline.

Abstract: Mechanisms are provided for performing an operation based on an identification of similar lines of questioning by input question sources. Question information identifying extracted features of an input question and a first source of the input question is obtained. A clustering operation is performed to cluster the input question with one or more other questions of a cluster based on a similarity of the extracted features of the input question to features of the one or more other questions. An operation is performed based on results of the clustering of the input question with the one or more other questions.

Abstract: An approach is provided for evaluating subject matter experts (SMEs) in a question and answering (QA) system. In the approach, a number of responses are received at the QA system with each of the responses being a response to a common question and each of the responses being received from a SME. One of the responses is selected with the selected response being from one of the SMEs that is being evaluated. The approach evaluates the selected response by comparing the selected response to the responses received from the other SMEs. Based on the evaluation, the approach updates a SME confidence score that corresponds to the selected SME.

Abstract: Mechanisms are provided in a data processing system for utilizing algorithms based on categories in a question answering system. The mechanisms capture a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to questions in respective question categories in a question answering system. The mechanisms determine sets of algorithms to use for respective question categories according to efficiency and correctness analysis. The mechanisms determine a question category of a given input question and execute a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question.

Abstract: Mechanisms for selecting questions for a cluster of questions to be used with a question and answer (QA) system are provided. An input question is received and analyzed to identify at least one feature of the input question. Clustering of the input question with one or more other questions in a cluster of questions based on the at least one feature of the input question is performed. Based on results of the clustering, a determination is made as to whether to include or reject the input question as part of the cluster of questions. In response to determining to include the input question as part of the cluster of questions, the cluster of questions is updated to include the input question. The updated cluster of questions is stored in a storage device associated with a data processing system.

Abstract: Mechanisms for generating an answer to an input question are provided. The mechanisms receive an input question and route the input question to a plurality of Question and Answer (QA) system pipelines. The mechanisms receive results of processing the input question from each QA system pipeline in the plurality of QA system pipelines. The results comprise one or more candidate answers to the input question and associated confidence scores. The mechanisms adjust, for each QA system pipeline, the confidence scores of the one or more candidate answers associated with the QA system pipeline based on one or more weighting factors. In addition, the mechanisms generate the answer to the input question based on the adjusted confidence scores of the one or more candidate answers for each QA system pipeline.