Abstract: A computer system automatically corrects a view of an image capture device. A view of an image capture device is adjusted by applying one or more modifications selected from a group of: a zoom modification, a pan modification, and a tilt modification, wherein the view is displayed at a client device during a viewing session and the one or more modifications are indicated by the client device. One or more corrective operations are applied to the adjusted view based on user input, wherein the one or more corrective operations include a rotational operation to correct the adjusted view. Subsequent operations based on the one or more corrective operations are applied during a subsequent viewing session with corresponding view settings. Embodiments of the present invention further include a method and program product for automatically correcting a view of an image capture device in substantially the same manner described above.

Abstract: A computer system automatically corrects a view of an image capture device. A view of an image capture device is adjusted by applying one or more modifications selected from a group of: a zoom modification, a pan modification, and a tilt modification, wherein the view is displayed at a client device during a viewing session and the one or more modifications are indicated by the client device. One or more corrective operations are applied to the adjusted view based on user input, wherein the one or more corrective operations include a rotational operation to correct the adjusted view. Subsequent operations based on the one or more corrective operations are applied during a subsequent viewing session with corresponding view settings. Embodiments of the present invention further include a method and program product for automatically correcting a view of an image capture device in substantially the same manner described above.

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 method, apparatus and computer program product for creating parse trees from mixed records is described. A mixed record is received including a first entry containing a first natural language phrase and a second entry containing a first structured data entry. Using the first natural language phrase, a first parse tree structure is created joining words in the first natural language phrase with natural links indicating their semantic relationship within the first natural language phrase. A first synthetic node is created which represents the first structured data entry. The first synthetic is joined to the first parse tree structure using a synthetic link to a node in the parse tree to produce a pseudo parse tree. The pseudo parse tree is sent to a question answer system for answering user queries by reference to the pseudo parse tree.

Abstract: A method includes: receiving a question including multiple foci; determining one or more passages (OMPs) that include one or more sets of candidate answers (OMSCAs) to the question; determining matchings between words in the question and words in the OMPs; determining skipngrams of the question (“first skipngrams”); determining one or more sets of skipngrams of the OMPs (“second skipngrams”); determining one or more matching numbers (OMMNs) for the second skipngrams by determining, for each set of the second skipngrams and using the matchings, a number of the first skipngrams that match skipngrams of the set of skipngrams; determining a feature input to a machine learning model (MLM) using the OMMNs; determining one or more answers (OMAs) to the question by determining, by the MLM, whether the OMSCAs are correct answers to the question based at least in part on the feature input; and sending the OMAs to a user device.

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: A method, system and computer program product are provided for implementing misleading title identification. A title and a list of passages are received. The title is supplied to a question answering factoid pipeline as a question. The title is analyzed against the list of passages or content as an answer source material. A respective answer score of all passages is compared with a tunable threshold to identify titles that are misleading or inaccurate based on the content of all passages. A selected action for the identified misleading titles is provided for a user.

Abstract: The disclosed embodiments include a Question and Answer (QA) system, computer program product, and computer-implemented method configured to adjust passage relevancy to a question based on time. The disclosed embodiments seek to improve the process of providing answers to questions that include a temporal reference. In particular, the disclosed embodiments are better able to provide answers to questions that include a temporal reference that does not have an exact matching temporal reference in an answer source of a QA system.

Abstract: An approach is provided in which an information handling system converts a first set of text to synthesized speech using a text-to-speech converter. The information handling system then converts the synthesized speech to a second set of text using a speech-to-text converter. In response to converting the synthesized speech to the second set of text, the information handling system analyzes the second set of text against a filtering criterion and prevents usage of the synthesized speech based on the analysis.

Abstract: A computer-implemented method that includes receiving a search query and, after receiving the search query, identifying a first subset of documents that include the search query by searching, based on the search query, an inverted index of a corpus of documents that includes the first subset of documents. The computer-implemented method additionally includes processing the first subset of documents to identify entities related to the search query and relations between the entities and the search query. The computer-implemented method additionally includes generating a knowledge graph based on the entities and the relations.

Abstract: A computer-implemented method includes receiving an input query including a comparative question referencing a plurality of entities. The comparative question includes a comparative term regarding a metric associated with the plurality of entities. The computer-implemented method includes generating a plurality of polar questions. Each of the plurality of polar questions seeks a polar answer to a comparison, along the metric and according to the comparative term, between a target entity of the plurality of entities and at least one second entity of the plurality of entities. The computer-implemented method includes determining confidence scores for the plurality of polar questions. The computer-implemented method includes identifying a particular polar question of the plurality of polar questions based on the confidence scores. The computer-implemented method includes outputting a response to the input query that identifies the target entity of the particular polar question as an answer to the input query.

Abstract: A system comprising a memory storing an inverted index of a corpus of documents, and a processor coupled to the memory and configured to receive a search query, after receiving the search query identify a first subset of documents that include the search query by searching, based on the search query, the inverted index of the corpus of documents, wherein the corpus of documents includes the first subset of documents, process the first subset of documents to identify entities related to the search query and relations between the entities and the search query, and generate a knowledge graph based on the entities and the relations.

Abstract: Current plagiarism checkers can determine if a document has extensively copied from another but these checkers fail when a document is filled with synonyms. The present invention offers a means of detecting plagiarism involving the use of synonyms or heaving paraphrasing. A source passage from a pertinent corpus is modified by generating augmented tokens which include synonyms for the various terms in the passage. Text analysis may be required to confirm the semantic meaning of a term. The modified passage may be a regular expression. The modified passage can then be compared to a suspect passage using a trigram scorer. If possible plagiarism is detected, an alert message is sent to a reviewer with the passage of interest, the source passage, and an identification of the related corpus.

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: 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 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-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 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.