Abstract: Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.

Abstract: A method includes receiving, by a question answering system having a confidence threshold, plural questions from one or more user devices. The method includes processing each one of the questions by: generating an answer to the one of the questions; determining a confidence score of the answer; in response to determining the confidence score is greater than the confidence threshold, increasing the confidence threshold and returning the answer to the user device that generated the one of the questions; and in response to determining the confidence score is less than the confidence threshold, decreasing the confidence threshold and not returning the answer to the user device that generated the one of the questions. The increasing the confidence threshold and the decreasing the confidence threshold are performed such that the question answering system returns answers for the plural questions at a frequency that approximates a pre-defined target answering frequency.

Abstract: Receive a question via a graphical user interface (GUI), obtain a passage of text potentially relevant to the question, and receive, via the GUI, a selection of a number of question-answering models to be ensembled. Produce a plurality of answers to the question by running a plurality of question-answering models, consistent with the selection of the number of question-answering models to be ensembled, on the passage of text. Produce an ensembled answer by ensembling the plurality of answers according to their respective confidence scores. Display, via the GUI, the ensembled answer in context of the passage of text, with the ensembled answer visually marked in the passage of text. Optionally, repeat these steps for a second passage of text.

Abstract: A method includes receiving, by a question answering system having a confidence threshold, plural questions from one or more user devices. The method includes processing each one of the questions by: generating an answer to the one of the questions; determining a confidence score of the answer; in response to determining the confidence score is greater than the confidence threshold, increasing the confidence threshold and returning the answer to the user device that generated the one of the questions; and in response to determining the confidence score is less than the confidence threshold, decreasing the confidence threshold and not returning the answer to the user device that generated the one of the questions. The increasing the confidence threshold and the decreasing the confidence threshold are performed such that the question answering system returns answers for the plural questions at a frequency that approximates a pre-defined target answering frequency.

Abstract: A method for determining an application error from a screenshot includes receiving, by a computing device, a computer application screenshot image indicating a computer error has occurred. The computing device analyzes the computer application screenshot image using a machine learning image analysis to determine one or more error regions in the computer application screenshot image. The computing device further processes the analyzed computer application screenshot to extract text from the one or more error regions in the computer application screenshot image. The computing device determines the application error based upon the extracted text. The computing device further automatically applies an automated error fix based upon the determined application error.

Abstract: A method modifies a social media post in response to determining that a hashtag for the social media post diverges from how the hashtag is used by other social media posts. A computing device receives a social media post, which contains a hashtag, and analyzes the social media post using natural language processing and a sentiment analysis to determine a sense and sentiment of the social media post. The computing device receives a plurality of reference social media posts, where each of the reference social media posts contains the hashtag, and utilizes the natural language processing and the sentiment analysis to determine a sense and sentiment of the reference social media posts. In response to determining that the sense and sentiment of the social media post do not match the sense and sentiment of the reference social media posts, the computing device causes the social media post to be altered.

Abstract: A method for determining an application error from a screenshot includes receiving, by a computing device, a computer application screenshot image indicating a computer error has occurred. The computing device analyzes the computer application screenshot image using a machine learning image analysis to determine one or more error regions in the computer application screenshot image. The computing device further processes the analyzed computer application screenshot to extract text from the one or more error regions in the computer application screenshot image. The computing device determines the application error based upon the extracted text. The computing device further automatically applies an automated error fix based upon the determined application error.

Abstract: A method modifies a social media post in response to determining that a hashtag for the social media post diverges from how the hashtag is used by other social media posts. A computing device receives a social media post, which contains a hashtag, and analyzes the social media post using natural language processing and a sentiment analysis to determine a sense and sentiment of the social media post. The computing device receives a plurality of reference social media posts, where each of the reference social media posts contains the hashtag, and utilizes the natural language processing and the sentiment analysis to determine a sense and sentiment of the reference social media posts. In response to determining that the sense and sentiment of the social media post do not match the sense and sentiment of the reference social media posts, the computing device causes the social media post to be altered.

Abstract: Systems and methods for generating answers to questions. One method includes receiving a question having question terms; identifying candidate answers to the question having answer terms; searching data sources to determine passages including either a question term or an answer term in the candidate answer; scoring the passages for candidate answers using a scoring mechanism, the scoring mechanism computing a first degree of relevance of the passage to the question terms, computing a second degree of relevance of the passage to the answer terms of one of the candidate answers, and determining a score for the passage by combining the first degree of relevance and the second degree of relevance; ranking candidate answers to the question based on the scores associated with the scoring each of the passages for each of the candidate answers; and providing an answer to the question based on ranking of the candidate answers.

Abstract: A method, system and computer program product are disclosed for searching for information using a knowledge base. In one embodiment, the method comprises receiving a query; formulizing the query, including dividing the query into a plurality of parts; for each of the parts, identifying a source, using the knowledge, that addresses that part; and combining the sources to answer the query. In one embodiment, the query includes text; the text is separated into a plurality of segments; and, for each of the segments, at least one source is identified addressing the segment. In an embodiment, a logical proof is formulated having a conclusion that is an answer to the query, and a sequence of statements that establish said conclusion; and a proof of this conclusion is generated by identifying two or more documents that assert the sequence of statements.

Abstract: A method, system and computer program product are disclosed for searching for information using a knowledge base. In one embodiment, the method comprises receiving a query; formulizing the query, including dividing the query into a plurality of parts; for each of the parts, identifying a source, using the knowledge, that addresses that part; and combining the sources to answer the query. In one embodiment, the query includes text; the text is separated into a plurality of segments; and, for each of the segments, at least one source is identified addressing the segment. In an embodiment, a logical proof is formulated having a conclusion that is an answer to the query, and a sequence of statements that establish said conclusion; and a proof of this conclusion is generated by identifying two or more documents that assert the sequence of statements.