International Business Machines Corporation

Malolan Chetlur

Shivkumar Kalyanaraman

Vijay Ekambaram

Ashok Pon Kumar Sree Prakash

Umamaheswari C Devi

Sharad C Sundararajan

Vikas V Joshi

Bikram Sengupta

Ravindranath Kokku

Partha Dutta

Mukesh Kumar Mohania

Vijay Arya

Parul Gupta

Ramana V Polavarapu

Aaron K Baughman

Peter Kenneth Malkin

Christian Eggenberger

Hemant Jagadish Kowshik

Kunal Korgaonkar

Robert Bruce Nicholson

Satyanarayana Venkata Nitta

Sumedh Wasudeo Sathaye

Prasenjit Dey

Smitkumar Narotambhai Marvaniya

Chalapathy Venkata Neti

Robert J Schloss

Renuka Sindhgatta

Mukundan Madhavan

Vinay Kumar Reddy

Ashay U Tamhane

Aakar Gupta

Anand Seetharam

Dinesh C Verma

Kuntal Dey

Sameep Mehta

Sougata Mukherjea

Praveen Jayachandran

Pankaj Satyanarayan Dayama

Vinayaka D Pandit

Vikrant Nandakumar

John Michael Tracey

Vikas Agarwal

Sumit Mittal

Danish Contractor

Pradipta De

Arvind Agarwal

Indrajit Bhattacharya

Arun Vishwanath

Zygmunt A Lozinski

Pooja Aggarwal

Sreyash Kenkre

Susan Patricia Paice

Prateeti Mohapatra

Stuart J Hayton

Tejas Indulal Dhamecha

Venkatadheeraj Pichapati

Sandipan Sarkar

Ayush Dubey

Harish Ganapathy

Hemant Jagdish Kowshik

Subhendu Dey

An apparatus is disclosed which includes at least one processing device comprising a processor coupled to a memory. The at least one processing device, when executing program code, is configured to: extract one or more entities identified in a plurality of data artifacts based at least in part on one or more datasets, extract one or more entities identified in a plurality of code artifacts based at least in part on the one or more datasets, extract one or more entities identified in a plurality of user interface artifacts based at least in part on the one or more datasets, generate a set of dependency graphs each based at least in part on one or more relationships among the respective extracted one or more entities, and perform one or more of a lexical analysis and a semantic analysis on the set of dependency graphs to identify a data domain of the one or more datasets.

Automatic data domain identification

Methods, systems and computer program products for automated learning are provided herein. A computer-implemented method includes authenticating a plurality of users for an automated learning session, wherein the plurality of users correspond to at least one device, and providing the automated learning session for the plurality of users. Providing the automated learning session comprises analyzing a plurality of learning models corresponding to one or more of the plurality of users, determining, based on the analysis, one or more activities to be performed by the plurality of users during the automated learning session, and executing the one or more activities on at least one device.

System and method for social learning utilizing user devices

One embodiment provides a method, including: identifying, utilizing one or more sensors operatively coupled to the smart device, a user operating a smart device; inferring, based upon the identifying the user, a knowledge level of the user with respect to the smart device; determining, based in part on the knowledge level of the user, at least one input within a plurality of inputs provided by the user is anomalous with respect to a pattern of inputs utilized to execute a command; transforming, based upon the anomalous at least one input and the pattern, the plurality of inputs to a plurality of inputs matching the pattern of inputs; and executing an action based upon the transformed plurality of inputs.

Executing actions based upon transformed inputs

An embodiment of the invention may include a method, computer program product and computer system for non-linear video navigation. The method, computer program product and computer system may include a computing device that collects source content and source content metadata from a content device. The computing device may extract the metadata from the source content and store the source content and the metadata on a server. The computing device may receive user profile data from a user device. The computing device may map the semantic data of the source content, the metadata, and the user profile data to a knowledge graph. The computing device may create navigational panels for navigating the source content based on the knowledge graph, the navigational panels enabling non-linear navigation of the source content by a user. The computing device may provide the navigational panels to the user device.

Non-linear navigation of videos

Methods, systems, and computer program products for content marshaling using biometric data are provided herein. A computer-implemented method includes estimating a cognitive state of a user based at least in part on analyzing one or more sets of biometric data pertaining to the user; dynamically compiling multi-modal content for the user based at least in part on (i) the estimated cognitive state of the user, (ii) one or more user parameters, and (iii) content availability information; and outputting the compiled content to the user via one or more devices.

Content marshaling using biometric data

Providing targeted, evidence-based recommendations to improve digital content quality, in one aspect, may include partitioning digital content into a sequence of logical content modules. Quality scores for the logical content modules along a plurality of quality dimensions may be determined. User interactions with the digital content on a user interface are monitored. Raw events generated from user interaction in accessing the digital content are captured. Raw event patterns for the logical content modules are detected. The raw event patterns of user interaction are transformed into a set of dynamic states representing potential user experience and performance. The set of dynamic states are associated with a respective logical content module. The quality dimensions of the logical content modules and associated quality scores are correlated with the dynamic states.

Providing targeted, evidence-based recommendations to improve content by combining static analysis and usage analysis

An example operation may include one or more of receiving an identification of vendor resources held by each of a plurality of members of a social network, extracting respective preference information of the plurality of members from web pages associated with the plurality of members on the social network, automatically determining to exchange resources of a first vendor issued to a first member of the social network with resources of a second vender issued to a second member of the social network based on extracted preference information of the first and second members, and triggering execution of the exchange of resources via one or more blockchain computing networks associated with the social network.

Cognitive determination system connecting social network and blockchain network

One embodiment provides a method, including: receiving input identifying a goal of a student, wherein the goal indicates (i) a target concept to be learned by the student and (ii) a desired expertise corresponding to the target concept; receiving input indicating constraints comprising (i) a time budget and (ii) an effort budget; and generating a syllabus for the student to reach the goal, wherein the syllabus comprises a sequence of sub-concepts to be learned for reaching the goal, by: producing a plurality of alternative sequences of sub-concepts for reaching the identified goal, each sequence of sub-concepts having both a determined, corresponding (i) effort cost and (ii) time cost, wherein determining the corresponding effort cost and time cost comprises identifying relationships between sub-concepts; and determining, from the plurality of alternative sequences, a particular one of the sequences that reaches the target concept at the desired expertise and fulfills the indicated constraints.

Personalized syllabus generation using sub-concept sequences

Methods and arrangements for determining at least one employment trait of an individual from online activity. Collecting a plurality of employment task data points from a plurality of online sources, wherein each employment task comprises a data set indicative of a path taken by at least one individual from a starting point to an ending point, wherein the starting point and ending point are defined on the basis of common parameters. The collected plurality of employment task data points are assessed, to determine an employment trend of the individual and creating at least one profile of the individual based on the determined employment trend. At least one profile is stored at a data storage location. Other variants and embodiments are broadly contemplated herein.

Determining working style and traits

Techniques for conditional presentation of auxiliary information are provided. In one example, a computer-implemented method comprises determining, by a device operatively coupled to a processor, feedback information for a user in response to a media presentation, wherein the feedback information is indicative of a mental state of the user during presentation of the media presentation. The computer-implemented method can further comprise determining content of the media presentation associated with the mental state of the user, and determining auxiliary information about the content based on the mental state of the user. The computer-implemented method can further comprise providing, by the device, the content to a user device during the presentation of the media presentation and for rendering at the user device in association with presentation of the content.

Conditional provisioning of auxiliary information with a media presentation

Techniques for generating auxiliary information for a media presentation are provided. In one example, a computer-implemented method comprises receiving, by a device operatively coupled to a processor, first feedback information for a group of users regarding mental states of the users during a media presentation. The computer-implemented method can further comprise determining, by the device, first parts of the media presentation considered confusing to at least some of the users and second parts of the media presentation considered interesting to at least some of the users based on the first feedback information, and generating, by the device, an index data structure comprising first information identifying the first parts and classifying the first parts as confusing and second information identifying the second parts and classifying the second parts as interesting.

Generating auxiliary information for a media presentation

Growing community of inventors

Bengaluru, India

Malolan Chetlur