International Business Machines Corporation

James William Murdock, Iv

David Angelo Ferrucci

Adam P Lally

John Martin Prager

Jennifer Chu-Carroll

Eric William Brown

James J Fan

David C Gondek

Wlodek Wlodzimierz Zadrozny

Radha Mohan De

Aditya Anand Kalyanpur

Sujoy Roy

Benjamin P Segal

Christopher Munjal Nolan

Nisarga Markandaiah

Anthony Tom Levas

Jiri Navratil

Mary Swift

Sai Prathyusha Peddi

Lin Pan

Rishav Chakravarti

Anastas Stoyanovsky

Eun Ha

Chung-Wei Hang

Kazi Hasan

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.

Unsupervised dynamic confidence thresholding for answering questions

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.

Application error analysis from screenshot

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.

Protecting a social media post with a hashtag from divergence

A method is provided that includes generating answer-passage pairs, each associated with a respective one of multiple feature vectors. The method includes, for each answer in the pairs, merging the feature vectors associated with any of the pairs that include the answer to obtain a merged answer vector. The method includes, for each passage in the pairs, (i) merging the feature vectors associated with any of the pairs that includes the passage to obtain a merged passage vector, (ii) merging the feature vectors from the merged answer vector for each answer that is associated with the passage via at least one of the pairs to obtain a merged passage-answer vector, and (iii) concatenating the merged passage vector and the merged passage-answer vector to obtain a concatenated passage vector. The method includes ranking the concatenated passage vector for each passage to obtain a ranked list of passages with associated confidence scores.

Ranking passages by merging features from factoid answers

A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

Providing answers to questions using logical synthesis of candidate answers

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.

Supporting evidence retrieval for complex answers

Embodiments may provide a computer implemented method in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to cause the processor to implement a system for bookmarking, the method comprising: receiving, by the processor, at least one search query from a user; returning, by the processor, a set of search results and a search score for each search result to the user; recording, by the processor, behavior of the user with respect to the search results; selecting, by the processor, at least one search result based on recorded behavior and the search score; determining, by the processor, at least one topic for the at least one selected search result; and generating, by the processor, a bookmark for each selected search result, under the at least one topic.

Intelligent bookmarking with cognitive capability

A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence 'score' or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.

Lexical answer type confidence estimation and application

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.

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Millwood, NY, United States of America

James William Murdock, Iv