Abstract: A skill-gap analysis and recommender system and method is described that serves as a personalized education and skill (PES) map. It provides a comprehensive presentation of the opportunities afforded by the University along with a detailed analysis of trends for placements and career goals. It conducts a comprehensive analysis of past student data and current market trends to make recommendations that are adapted to each student's profile in line with their individual career goals. This is accomplished using an algorithm for adaptive association pattern mining with a built-in mechanism for creation of meta-categories and drill-down for specifics, so as to meet the needs of every student and not miss infrequent patterns or rare opportunities afforded by the system. For the recommendations generated, the system also provides an assessment of the time-sensitivity of a goal and a mechanism for students to track their progress through prioritizing short and long term goals.

Abstract: Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.

Abstract: Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.

Abstract: A computer implemented method and system for assisting a user to learn and/or communicate in a visual communication language in one or more modes is provided. The multimodal communication assist application, provided on a user's computing device, determines the user's characteristic information based on one or more selected multimodal communication mappers. The multimodal communication assist application determines a delay factor based on the characteristic information. The multimodal communication assist application captures a modal input in one of the modes from the user via an interactive interface based on the delay factor and the characteristic information. The multimodal communication assist application processes and transforms the captured modal input in one of the modes into a modal output in another one or more of the modes and renders the modal output to the user via the interactive interface.

Abstract: A computer implemented method and system for assisting a user to learn and/or communicate in a visual communication language in one or more modes is provided. The multimodal communication assist application, provided on a user's computing device, determines the user's characteristic information based on one or more selected multimodal communication mappers. The multimodal communication assist application determines a delay factor based on the characteristic information. The multimodal communication assist application captures a modal input in one of the modes from the user via an interactive interface based on the delay factor and the characteristic information. The multimodal communication assist application processes and transforms the captured modal input in one of the modes into a modal output in another one or more of the modes and renders the modal output to the user via the interactive interface.