Abstract: A computer-implemented method, computer program product, and system is provided for determining requirements for testing software. In an implementation, a method may include inspecting contents of a test case, including source code of the test case. The method may also include identifying at least one of: at least one characteristic of a test machine and at least one characteristic of a resource required to execute the test case correctly. The method may further include compiling a list of requirements for the test case to execute correctly based upon, at least in part, the at least one of the at least one characteristic of the test machine and the at least one characteristic of the resource.

Abstract: A computer-implemented method, computer program product, and system is provided for determining requirements for testing software. In an implementation, a method may include inspecting contents of a test case, including source code of the test case. The method may also include identifying at least one of: at least one characteristic of a test machine and at least one characteristic of a resource required to execute the test case correctly. The method may further include compiling a list of requirements for the test case to execute correctly based upon, at least in part, the at least one of the at least one characteristic of the test machine and the at least one characteristic of the resource.

Abstract: Resource provisioning information links to resource provisioning information of at least one reusable component resource that satisfies at least a portion of user-specified resource development constraints of a new resource under development are identified within a resource provisioning-link registry. Using the identified resource provisioning information links, the resource provisioning information of the at least one reusable component resource is programmatically collected from at least one data provider repository that stores reusable resources and that publishes the resource provisioning information links to the resource provisioning-link registry. The programmatically-collected resource provisioning information of the at least one reusable component resource is analyzed.

Abstract: A mechanism is provided for secure automated parcel delivery. A first device owned and controlled by a recipient entity to whom a physical item is being delivered receives a delivery communication code. The recipient entity and through the first device determines a delivery policy data set indicative of a manner in which the physical item is to be delivered. Responsive to the detection that the physical item is being delivered to a designated delivery zone where the physical item will be received by the recipient entity, the first device wirelessly authenticates to a second. device controlled by a sender entity using the delivery communication code. Responsive to the authentication of the first device to the second device, the first device wirelessly communicates to the second device the delivery policy data set.

Abstract: Resource provisioning information links to resource provisioning information of at least one reusable component resource that satisfies at least a portion of user-specified resource development constraints of a new resource under development are identified within a resource provisioning-link registry. Using the identified resource provisioning information links, the resource provisioning information of the at least one reusable component resource is programmatically collected from at least one data provider repository that stores reusable resources and that publishes the resource provisioning information links to the resource provisioning-link registry. The programmatically-collected resource provisioning information of the at least one reusable component resource is analyzed.

Abstract: A method, system and computer-usable medium are disclosed for automating the generation of table-based groundtruth, comprising: receiving a document comprising unstructured text and a table; generating questions by applying a template the contents of the table; performing QA pair generation operations on the table to generate QA pairs, each QA pair comprising a question generated by applying the template; and, assigning a score to each QA pair, the score providing an indicator of user interest to each QA pair, the score being based on a score generation methodology using the unstructured text and the table.

Abstract: A method, system and computer-usable medium are disclosed for using table-based groundtruth to train a question-answer (QA) system, comprising: receiving a corpus of text comprising unstructured text and a table; performing QA pair generation operations on the unstructured text and the table to generate QA pairs, the QA pairs being based upon information obtained from the table; assigning a score to each QA pair, the score corresponding to an indicator of user interest.

Abstract: A method for controlled sharing, in a cognitive computing system having a memory and a processor, of content from a variety of content providers may include receiving, by the cognitive computing system, an inquiry, wherein the inquiry is directed to at least one content topic. The method may then include identifying, by the cognitive computing system, the at least one content topic, and determining that a cognitive component of the cognitive computing system managed by a content provider has access to a content repository addressing the at least one content topic. The method may further include distributing, by the cognitive computing system, the inquiry to the cognitive component. The method may additionally include receiving a response from the cognitive component.

Abstract: A knowledge graph is built based on a corpus stored in the computer system. The corpus includes a set of events and each event includes a respective set of entities. A first set of entities is identified in the NLQ. The first set of entities is used to identify a first set of significant events in the selected corpus in a first search depth. A second set of entities is identified in the first set of significant events. The knowledge graph determines which ones of the second set of entities are related to the entities in the first set of entities to produce a filtered second set of entities. The filtered second set of entities is used to identify a second set of significant events in the selected corpus in a second search depth. Members of the first and second set of significant events are presented to a user.

Abstract: Clustering a set of natural language queries NLQs based on a set of significant events retrieved from a corpus stored in a computer system is described. A set of NLQs is used by a search engine for searching a selected corpus to retrieve respective sets of significant events. The set of NLQs is clustered into a plurality of NLQ clusters according to a threshold number of common significant events being returned by the search engine for respective members of an NLQ cluster.

Abstract: An approach is provided in which a knowledge manager identifies first opinion phrases included in a first review that the knowledge manager displays on a display. The knowledge manager locates contradictory reviews that include second opinion phrases that contradict the first opinion phrases and, in turn, displays the contradictory reviews on the display.

Abstract: A method, executed by a computer, includes prompting a user to speak an utterance comprising one or more words, recording a user speaking the utterance to produce recorded speech, converting the recorded speech to recognition data, and selecting a next utterance based on the recognition data and personality information for the user. The next utterance may be selected from a library of utterances. Selecting a next utterance may include selecting an action such as repeating, rephrasing, contrasting, elaborating, summarizing, providing a different context, and adjusting a difficulty level. A computer system and computer program product corresponding to the above method are also disclosed herein.

Abstract: A method, executed by a computer, includes receiving a personality profile for a user, prompting a user to speak an utterance comprising one or more words, wherein the utterance is selected from a library of utterances based on the personality profile for the user, and converting a recording of a user speaking the utterance to recognition data. The method may also include selecting a next utterance based on the recognition data and the personality profile for the user. The next utterance may be selected from a library of utterances. Selecting a next utterance may include selecting an utterance corresponding to an action such as repeating, rephrasing, contrasting, elaborating, summarizing, providing a different context, and adjusting a difficulty level. A computer system and computer program product corresponding to the above method are also disclosed herein.

Abstract: A computing device comprising a processor configured to receive a natural language search query and determine a first response to the natural language search query, the first response having a first confidence level. The processor is further configured to determine a sensor class effecting an information gain on the natural language search query according to a table of training data. The processor is further configured to augment the natural language search query to form an augmented search query according to data received from at least one sensor that is a member of the sensor class and determine a second response to the augmented search query, the second response having a second confidence level. The processor is further configured to store information to the table of training data that associates the at least one sensor with a value of a change between the first confidence level and the second confidence level.

Abstract: An approach is provided that analyzes electronic documents, each of which was written by an author. Time-based personality profiles are retrieved corresponding to the author. A date of each of the electronic documents is compared to a set of dates corresponding to different personality insights of the author over time. The approach selects one of the author's personality insights based on the comparison. A sentiment score corresponding to each of the electronic documents is adjusted based on the selected personality insight that corresponds to each of the electronic documents.

Abstract: An approach is provided that analyzes electronic document sets, each of the sets written by a different author. The analysis includes performing a normalized sentiment analysis of the documents which results in normalized sentiment scores that pertain to each of the authors. The normalize sentiment scores are stored in a data store that is accessible from a question answering (QA) system. The question answering system then receives a sentiment-based question. Responsively, the QA system generates a qualitative set of candidate answers, with the candidate answers based at least in part on the normalized sentiment scores retrieved from the data store.

Abstract: A computing device and method is usable to augment search queries with data obtained from sensors. The computing device comprises a processor configured to receive, from a query source, a search query comprising a query concept. The processor is further configured to determine a context of the query concept expressed in the query. The processor is further configured to determine a response to the query. The processor is further configured to validate the context of the query using at least one sensor. The processor is further configured to transmit the response to the query to the query source.

Abstract: A method for ground truth generation includes providing training questions to a machine learning system executing on a computer. The machine learning system generates candidate answers to each of the training questions. The method also includes providing the candidate answers to a plurality of subject matter experts for evaluation with respect to the training questions, wherein the evaluation comprises assignment of an SME relevance score to each of the candidate answers. The method further includes analyzing each of the candidate answers with respect to a plurality of scoring features, wherein each of the scoring features is indicative of quality of the candidate answer. The method yet further includes generating a ground truth metric value that indicates a measure of agreement between the subject matter experts relative to a measure of agreement between results of the analyzing.

Abstract: A method for training a question answering system includes providing training questions to a question answering system executing on a computer and to a plurality of subject matter experts. The question answering system generates first answers to each training question. Second answers to the training questions are received from the subject matter experts. Feature scores for each of the first answers and the second answers are generated and compared across the second answers and the first answers. Each of the feature scores is representative of a quality of an answer that is indicative of relevance to a corresponding training question. Based on the comparing, a measure of consistency of the feature scores of the second answers is determined, and a measure of consistency of the feature scores of the second answers to the first answers is determined. The measures of consistency are transmitted to the subject matter experts.

Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of different summaries for a single instance of content, calculating a relevancy score for each of the plurality of different summaries, and selecting one of the plurality of different summaries, based on the relevancy score for each of the plurality of different summaries.