International Business Machines Corporation

Radha Mohan De

Swaminathan Balasubramanian

Indrajit Poddar

Cheranellore Vasudevan

Ashley Dallas Delport

Sujoy Roy

Brian M O'Connell

Keith R Walker

James William Murdock, Iv

Saswati Maji

Kristin E McNeil

James W Murdock, Iv

Itai Gordon

Benjamin P Segal

John Martin Prager

Mary Swift

Diptiman Dasgupta

Sibasis Das

Jian Wu

Krisha Banerjee

Christopher Munjal Nolan

Suman Patra

Mamnoon Jamil

Miriam Nizri

Karina Elayne Kervin

Somnath Das

Nisarga Markandaiah

Rajib Das

Jaymin Desai

Dhruv Khurana

Caesar Chatterjee

Sneha Srinivasan

Priyankar Malakar

Indrajit Kanjilal

Salmali Baksi

Baishali Ghosal

Shivalik Chakravarty

Krishnendu Chowdhury

Various systems and methods are presented regarding automatically generating a document for a particular topic, and further utilizing an algorithm to automatically identify information in a resource that pertains to the topic. The document can be a purpose-specific document, created by a template configured to combine data fields to build the document. Each data field can be subject-matter specific with an associated algorithm. The algorithm can be trained to recognize and extract content that potentially meets the subject matter of the data field. The data field can be populated with the content. Subsequent editing of the content populating the data field can be monitored to determine an effectiveness of the algorithm to identify data of interest in the data repository. In the event of low success, the algorithm can be retrained. Further, the document can be regenerated if an algorithm is retrained, new information added to the repository, etc.

Automated document harvesting and regenerating by crowdsourcing in enterprise social networks

A method includes preparing key actions in a process design document (PDD) from historical PDD documents by tokenizing the PDD with part-of-speech (POS) grammar against key verbs and phrases, extracting automation unit pairs from the historical process documents to map the automation unit pairs with the key verbs and phrases, constructing a set of automation tasks against one or more of the key verbs and phrases, coupling different process models with domain verbs for the phrases to mark one or more of the automation unit pairs as actions against one or more of the key verbs, constructing a tree-like mapping where each key action points to different actions in a target specific automation language, and defining a vocabulary interface of a domain specific language (DSL) by using the key actions and phrases.

RPA development acceleration using DSL validator

Detecting duplicate tables by converting relational tables to knowledge graphs; and mapping nodes in the knowledge graphs to sources in the relational tables. The method may further include applying graph matching to the knowledge graphs; and assessing degree of matching between matched knowledge graphs.

Detecting duplicate tables in data lake databases

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.

Generating alerts on demand for participants in multiparty discussion channels

A method, computer system, and a computer program product for historical image search is provided. The present invention may include receiving an image search criteria. The present invention may also include generating a composite image search query based on the received image search criteria. The present invention may further include searching for a matching historical image based on the generated composite image search query. The present invention may also include returning a historical image search result.

Historical image search

Provided is a method, computer program product, and system for mitigating user dissatisfaction with a product. A processor may collect a first set of user interaction data and a first set of user sentiment data related to the product. The processor may generate a user profile for the user, including a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data. The processor may monitor a second set of user interaction data and a second set of user sentiment data. The processor may compare the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold and determine that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded. In response, the processor may output an action to reduce dissatisfaction of the user.

Mitigating user dissatisfaction related to a product

In an approach for enhancing an experience of a user listening to and/or watching an audio-visual content by modifying future audio and/or video frames of the audio-visual content, a processor captures a set of sensor data from an IoT device worn by the first user. A processor analyzes the set of sensor data to generate one or more connotations by converting the emotion using an emotional vector analytics technique and a supervised machine learning technique. A processor scores the one or more connotations on a basis of similarity between the emotion exhibited by the first user and an emotion expected to be provoked by a second user. A processor determines whether a score of the one or more connotations exceeds a pre-configured threshold level. Responsive to determining the score does not exceed the pre-configured threshold level, a processor generates a suggestion for the producer of the audio-visual content.

Automatic connotation for audio and visual content using IOT sensors

A method for receiving a historical incident data set with the historical incident data set including a plurality of data records, for each given data record of the plurality of data records, applying a causal analysis algorithm to determine a set of causal factor(s) for the historical instance of an incident corresponding to the given data record to obtain a problems and solutions data set, and automatically, and by machine logic, generating a chatbot based, at least in part, on the problems and solutions data set.

Automatic chatbot generation through causal analysis of historical incidents

An illustrative resolution is generated using a computer for a reported operational issue while using a computer system. A learning model is developed using the computer to facilitate resolving an operational error of a computer system. The learning model can include generating an error report, based on tracking user inputs into a computer system and a plurality of state transitions of the computer system, respectively, when the operational error is not resolved by the user inputs. An error screenshot for each operational step associated with the user inputs is generated. A state transition is cross referenced to a corresponding operational step, and to a best practice in a user's manual, respectively. A deviation of an operational step from a best practice in the user's manual, respectively, is generated. An error screenshot is marked illustratively to show the deviation from the best practice in comparison to the operational step.

Computer generation of illustrative resolutions for reported operational issues

A client device can receive, from a data processing system, first data, the first data selected by the data processing system based on second data generated by at least one IoT device with which the client device is associated, and the first data indicating at least one advertisement. The client device can access the at least one advertisement using the first data indicating the at least one advertisement. The client device can add the at least one advertisement to the content accessed by the client device. The client device can present the content with the at least one advertisement added to the content.

Personalization of advertisement selection using data generated by IoT devices

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

Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises generating a first user workplan based on received input; automatically modifying the first user workplan based on subsequent received input, wherein automatically modifying the first user workplan comprises comparing the first user workplan to a performance baseline workplan for a user computing device, measuring a deviation between the performance baseline workplan and the first user workplan; and generating a second user workplan based on any modifications made.

Intelligent social IoT work plan

The capture and search of application properties for applications installed on virtual machines, includes obtaining a plurality of logs on a plurality of virtual machine images coupled to a network. For each given virtual machine image of the plurality of virtual machine images, the method includes: obtaining one or more logs on the given virtual machine image of the plurality of virtual machine images; analyzing each given log of the one or more logs to identify one or more concepts related to a set of application properties for one or more applications installed on the given virtual machine image; associating the one or more concepts and the set of application properties with an identity of the given virtual machine image; and storing the association of the one or more concepts and the set of application properties with the identity of the given virtual machine image in a virtual machine catalogue.

Capture and search of virtual machine application properties using log analysis techniques

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

Embodiments for enhancing privacy and security of an image by a processor. Metadata associated with the image is configured with a usage designation, the usage designation having accompanying notification information for notifying an owner of the usage designation if a condition of the usage designation is met.

Growing community of inventors

Howrah, India

Radha Mohan De