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: 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: Mechanisms are provided for implementing a virtual corpus engine that receives an inquiry to be processed and analyzes the inquiry to extract one or more features of the inquiry. The virtual corpus engine selects a weight matrix associated with a virtual corpus based on the extracted one or more features of the inquiry. The virtual corpus comprises a plurality of actual corpora of information. The weight matrix comprises a separate weight value for each actual corpus in the plurality of actual corpora. The virtual corpus engine processes the inquiry using a set of selected actual corpora selected from the plurality of actual corpora based on the weight values in the weight matrix and receives results of the processing of the inquiry using the set of selected actual corpora. The virtual corpus engine outputs the results of the processing of the inquiry.

Abstract: According to one exemplary embodiment, a method for generating an answer in a question answering system is provided. The method may include receiving a question. The method may also include identifying a candidate answer from a corpus. The method may then include determining a plurality of sentences based on the identified candidate answer. The method may further include calculating a similarity value for each sentence within the plurality of sentences based on comparing the plurality of sentences to the candidate answer and the received question. The method may also include identifying at least one sentence within the plurality of sentences with a calculated similarity value that exceeds a threshold value. The method may then include generating the answer based on the candidate answer and the identified at least one sentence.

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: Sentiment scores for a first set of text can be normalized based on a statistical measure of sentiment of a corpus of text authored by a set of authors having respective personality profiles similar to a personality profile of an author of the first set of text. The set of authors can be grouped in a first cluster based on a range of at least one metric of a personality profile. A plurality of respective sentiment scores for portions of the corpus can be generated for the first cluster. A statistical measure of the plurality of respective sentiment scores can be generated. The plurality of respective sentiment scores can be normalized based on the statistical measure. The plurality of respective normalized sentiment scores can be applied to the first set of text to generate one or more sentiment scores for the first set of text.

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

Abstract: Mechanisms are provided for implementing a virtual corpus engine that receives an inquiry to be processed and analyzes the inquiry to extract one or more features of the inquiry. The virtual corpus engine selects a weight matrix associated with a virtual corpus based on the extracted one or more features of the inquiry. The virtual corpus comprises a plurality of actual corpora of information. The weight matrix comprises a separate weight value for each actual corpus in the plurality of actual corpora. The virtual corpus engine processes the inquiry using a set of selected actual corpora selected from the plurality of actual corpora based on the weight values in the weight matrix and receives results of the processing of the inquiry using the set of selected actual corpora. The virtual corpus engine outputs the results of the processing of the inquiry.

Abstract: Sentiment scores for a first set of text can be normalized based on a statistical measure of sentiment of a corpus of text authored by a set of authors having respective personality profiles similar to a personality profile of an author of the first set of text. The set of authors can be grouped in a first cluster based on a range of at least one metric of a personality profile. A plurality of respective sentiment scores for portions of the corpus can be generated for the first cluster. A statistical measure of the plurality of respective sentiment scores can be generated. The plurality of respective sentiment scores can be normalized based on the statistical measure. The plurality of respective normalized sentiment scores can be applied to the first set of text to generate one or more sentiment scores for the first set of text.

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 embodiment of the invention may include a method, computer program product and computer system for neural activity interpretation. The method, computer program product and computer system may include a computing device that presents a first user with a stimulus and monitors and maps the neural activity of the first user. The computing device may receive the first user's verbal reaction to the stimulus and map the linguistic data of the first user's verbal reaction to form a high dimensional vector based on the relationships of the mapped neural activity and the mapped verbal reaction of the first user. The computing device may associate the high dimensional vector with the stimulus presented resulting in a thoughts model. The computing device may receive a second user's neural activity and compare that second user's neural activity to the thoughts model to identify the neural activity in the second user.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for neural activity interpretation. The method, computer program product and computer system may include a computing device that presents a first user with a stimulus and monitors and maps the neural activity of the first user. The computing device may receive the first user's verbal reaction to the stimulus and map the linguistic data of the first user's verbal reaction to form a high dimensional vector based on the relationships of the mapped neural activity and the mapped verbal reaction of the first user. The computing device may associate the high dimensional vector with the stimulus presented resulting in a thoughts model. The computing device may receive a second user's neural activity and compare that second user's neural activity to the thoughts model to identify the neural activity in the second user.

Abstract: According to one exemplary embodiment, a method for generating an answer in a question answering system is provided. The method may include receiving a question. The method may also include identifying a candidate answer from a corpus. The method may then include determining a plurality of sentences based on the identified candidate answer. The method may further include calculating a similarity value for each sentence within the plurality of sentences based on comparing the plurality of sentences to the candidate answer and the received question. The method may also include identifying at least one sentence within the plurality of sentences with a calculated similarity value that exceeds a threshold value. The method may then include presenting the answer, whereby the answer comprises the plurality of sentences, the candidate answer, and metadata.

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: 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 for interpreting interpersonal communication includes monitoring a first interaction between two or more individuals using a set of monitoring devices including a camera, a microphone, and the like. A culture and personality type of at least one individual is identified based on the monitored first interaction. First cultural/personality profile information specific to the identified culture and personality type is retrieved from a database of cultural/personality profile information. A second interaction between the two or more individuals is monitored using the set of monitoring devices. A first facial expression, gesture, vocal intonation, or indication of emotional state derived from biometric data of the at least one individual is identified based on the monitored second interaction. The identified first expression is interpreted using the first cultural/personality profile information. The interpretation of the identified first expression is communicated to a user.

Abstract: A processor-implemented method, system, and/or computer program product sorts and displays product reviews of ecommerce products. One or more processor(s) receive product reviews for different types of ecommerce products from product reviewers. Reviewer profiles of the product reviewers, a biometric reading for a user from a biometric sensor, and a geophysical location reading for the user from a geophysical sensor are received. The biometric reading and the geophysical location reading are utilized to define a user profile of the user. The user profile is matched to a specific reviewer profile of a specific product reviewer from the product reviewers. The product reviews are sorted according to the different types of ecommerce products and the specific reviewer profile, visually modified based on the defined user profile, then displayed on an ecommerce webpage.

Abstract: A processor-implemented method, system, and/or computer program product sorts and displays product reviews of ecommerce products. A system receives product reviews for ecommerce products. The product reviews are displayed on an ecommerce webpage, are generated by product reviewers, and are for different types of products. Reviewer profiles of the product reviewers are received. The reviewer profiles include characteristics of the product reviewers that affect usage of one or more of the different types of products. A user profile for a user is received. The user profile includes characteristics of the user that affect usage of one or more of the different types of products. The user profile is matched to a specific reviewer profile from the reviewer profiles. The product reviews are sorted according to the different types of products and the specific reviewer profile. The sorted product reviews are then displayed on the ecommerce webpage.

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.