Abstract: An approach is provided that receives words that are input by a user of an application with the words being displayed on a display device. Each of the words are compared to words from a dictionary. Based on the comparisons, words that are not found in the dictionary and only appear a single time are highlighted as being misspelled words. However, words that are not in the dictionary but appear multiple times in the document are highlighted differently to indicate that these words are possible misspelled words with the difference in highlighting allowing the user to easily discern between misspelled and possibly misspelled words.

Abstract: A method, system and computer program product are provided for implementing unstructured content utilization from a structured source in a system capable of answering questions. A question is received by the system. The question is provided as a list of tokens T (T1, T2, . . . , Tn). A structured source is received containing records R (R1, R2, . . . , Rk). Headers H (H1, H2, . . . , Hi) are mapped to records. Each record R1, R2, . . . , Rk is searched for any token Ti in the list of tokens T (T1, T2, . . . , Tn) in the question. Responsive to identifying the token Ti in the question in a record Rj, the token Ti is added to a tracking structure. Any header mapped to the record Rj is compared to the list of tokens T (T1, T2, . . . , Tn) in the question. Responsive to identifying a header Hj mapped to the record Rj in the question, the header Hj is added to tracking structure.

Abstract: A computer-implemented method includes receiving a query referencing entities, and determining non-polar questions (NPQs) for the query. Each of the NPQs omits a respective target entity (TE) of the entities. The method includes determining, for each of the NPQs, whether the NPQ is a non-matching NPQ by determining whether a top ranked answer for the NPQ matches the TE of the NPQ. The method includes proceeding to determine an updated input statement (UIS) for a non-matching NPQ by replacing the TE of the non-matching NPQs with the top ranked answer for the non-matching NPQ, determine an updated NPQ for the UIS, and determine whether the top ranked answer for the updated NPQ matches the TE of the updated NPQ, in an iterative or recursive manner. The method includes outputting a UIS as a substitute statement for the query.

Abstract: A computer-implemented method includes dividing a textual representation of a media content into a plurality of portions separated at temporal boundaries of the media content and performing an analysis of each portion of the plurality of portions of the textual representation of the media content to determine a characteristic associated with each respective portion of the textual representation of the media content, generating a multi-dimensional model assigning each determined characteristic to each associated respective portion of the plurality of portions of the textual representation of the media content, the multi-dimensional model identifying each determined characteristic and the temporal boundaries to enable control of an environmental control device to modify an environment proximate to a user based on the multi-dimensional model, and transmitting the multi-dimensional model to a user equipment configured to control the environmental control device to modify the environment proximate to the user base

Abstract: A computer converts a question received in a natural language format into a string of text elements. The computer searches a corpus comprising unstructured passages with the string of the text elements as search terms to identify a selection of unstructured passages from the corpus relevant to the text elements. The computer annotates the selection of relevant unstructured passages with one or more annotations according to at least one natural language annotation type to generate an annotated selection knowledge base. The computer modifies the string of text elements by annotating at least one of the text elements according to the at least one natural language annotation type. The computer searches the annotated selection knowledge base using the modified string of text elements to generate a selection of ranked passages. The computer identifies an answer to the question based on the selection of ranked passages.

Abstract: A computer system evaluating an input segment of a communication, in parallel, by a baseline classification model trained with baseline passages indicating dictionary meaning and multiple generative sequence models each trained to classify a particular passage from among multiple indirect passages indicating usage with an indirect meaning, to receive a separate score from the baseline classification model and each of the generative sequence models, each separate score indicating a classification probability for the input segment. The computer system, responsive to one or more particular scores generated by one or more of the generative sequence models exceeding a baseline score generated by the baseline classification model summed with a tuning factor, flagging the input segment as having a potentially indirect meaning.

Abstract: Mechanisms are provided to minimize personally identifiable information (PII) in an electronic document. An iterative personally identifiable information minimization (IPIIM) engine receives an electronic document comprising natural language content having a mention of a protected entity and obfuscates the mention of the protected entity to thereby generate a minimized natural language content. A question answering system processes the minimized natural language content to generate a listing of candidate answers and corresponding confidence scores and the IPIIM engine determines whether or not the minimized natural language content is sufficiently obfuscated based on the listing of candidate answers and corresponding confidence scores. In response to determining that the minimized natural language content is sufficiently obfuscated, the minimized natural language content is provided for processing by a requestor computing device.

Abstract: A method trains and utilizes an artificial intelligence (AI) system. The AI system receives a question that has contextual features. The method trains the AI system to identify entries in a corpus that have one or more of the contextual features from the question. The method further trains the AI system to: form a set of answers to the question based on identified contextual entries in the corpus; identify and name an entry in the corpus that has a highest quantity of contextual features that match the contextual features in the question as an initial answer to the question; identify and merge multiple other answers to the question from the corpus; and replace the initial answer with the merged answer in order to create a fully trained AI system. The fully trained AI system is then utilized to answer the question with the merged answer.

Abstract: Embodiments for answering questions utilizing multiple models are described. A plurality of models is received. Each of the plurality of models is associated with answering questions for a respective user. A weighting is assigned to each of the plurality of models. An answer to a question is generated based on the plurality of models and the weighting assigned to each of the plurality of models.

Abstract: Embodiments relate to an intelligent computer platform to identify and evaluate candidate passages response data in natural language form. A passage is analyzed by applying input tokens against passage tokens. A structure representing the analyzed passage is populated with of matching input and passage tokens. The input and passage tokens are used to assess the leveraged structure. First and second counts of token matching criteria are determined, including a first count of matching token entries and a second count of evaluated token entries. An alignment of the passage to a candidate question is calculated and a ratio of the first and second counts assessed. Data from the passage is returned with the ratio.

Abstract: Embodiments relate to an intelligent computer platform to identify and evaluate candidate passages response data in natural language form. Natural language processing is applied to analyze a passage against one or more input tokens to identify matching content. A structure representing the analyzed passage is populated with of matching input and passage tokens. A first count of matching token entries and a second count of evaluated token entries are determined and qualified by closeness criteria. An alignment of the passage to a candidate question is calculated, including assessing a ratio of the first and second counts as a confidence value. Matching passage data is return from the passage with the confidence value.

Abstract: A mechanism is provided for routinely evaluating an accuracy of a request processing pipeline. A set of questions is executed through the request processing pipeline, producing a list of answers, supporting documents, and accuracy metrics. A determination is made as to whether a document contribution value of each document associated with the answer is equal to or above a document contribution threshold value. For those documents equal to or above the document contribution threshold value, a snapshot is stored in a training-data data structure. Based on a clustering of questions, for each question cluster, a determination is made of an average accuracy metric. A comparison is performed and a determination is made as to whether an accuracy metric delta exceeds the accuracy metric threshold value. If so, a differential report is generated indicating a review is needed of a training of the request processing pipeline.

Abstract: Embodiments relate to a computer platform and corresponding process and program code to assess multimedia files with respect to similarity and duplicate media content. Data streams are converted into sequences of events, and object representation within the streams is identified and subject to processing with respect to the event sequences. A similarity assessment is conducted between two or more of the data streams, and a corresponding distance measurement to quantify similarity is produced. Duplicate data is selectively identified in response to the similarity assessment and the produced distance measurement.

Abstract: Embodiments relate to a computer platform and corresponding process and program code to assess multimedia files with respect to similarity and duplicate media content. Data streams are converted into sequences of events, and audio representation with in the streams is identified and subject to processing with respect to the event sequences. A similarity assessment is conducted between two or more of the data streams, and a corresponding distance measurement to quantify similarity is produced. Duplicate data is selectively identified in response to the similarity assessment and the produced distance measurement.

Abstract: Embodiments for managing the utilization of software releases are provided. Information associated with a software release and at least one early adopter of the software release is analyzed to calculate a severity score for the software release. A time to utilize the software release is determined based on the calculated severity score.

Abstract: An approach is provided that receives a question at a question-answering (QA) system. The received question includes one or more terms, and the question pertains to a subject matter domain that is supported by the QA system. Analyzing a number of expressions included in a set of question-answer pairs (QA pairs), with the QA pairs being ground-truths established to in support of the subject matter domain. The analysis identifies whether a selected term from the question is a synonym for any of the expressions. The expressions that are identified as synonyms are then used in a QA pipeline that generates one or more candidate answers to the received question.

Abstract: Embodiments provide a computer implemented method for identifying and correcting a misspelling in a question answering (QA) system, wherein the QA system is coupled to a document corpus, and the document corpus includes a plurality of documents related to a particular domain. The method includes the following steps: receiving an input question and a plurality of passages, wherein the plurality of passages are extracted from the document corpus by the QA system; providing at least one alternate form for each token extracted from the input question and the plurality of passages; identifying at least one misspelled token; and scoring at least one alternate form of each identified misspelled token.

Abstract: A method determines a relevancy of answers to questions based on token relevance in a system capable of answering questions. One or more processors receive a question that is composed of a set of tokens T (T1, T2, . . . , Tn). The processor(s) select tokens T? (T?1, T?2, . . . , T?m) from the tokens T (T1, T2, . . . , Tn), where each T?j from T? is a noun, and classify each T?j as a noun type. The processor(s) scan a corpus to identify passages with candidate answers to the question, and analyze the identified passages utilizing noun entries in the passages classified as the noun type. The processor(s) train an artificial intelligence (AI) system to associate a relevancy to the question for the identified passages based on noun types, and then utilize the trained AI system to provide an answer to the question based on an output of the trained AI system.

Abstract: Embodiments relate to an intelligent computer platform to use ground truth data to rate source reliability, and application of the source reliability. A computer system, computer program product, and computer implemented method apply the ground truth data to evaluate a source, assess source reliability, and dynamically apply the assessed reliability. The assessed reliability is dynamically applied to response data, with the application yielding selective presentation of the response data based on the applied reliability assessment.

Abstract: Embodiments relate to an intelligent computer platform to use ground truth data to rate source reliability, and application of the source reliability. A computer system, computer program product, and computer implemented method apply the ground truth data to evaluate a document and statements therein, and dynamically apply the assessed reliability. The assessed reliability is dynamically applied to a source, with the application yielding acceptance of the document to the source based on the applied reliability assessment.