Context-Based Content Aggregation For Social Life Networks

Speaker: Maneesh Mathai

Affiliation: University of Western Sydney

Time: Monday 24/02/2014 from 14:00 to 15:00

Venue: Access Grid UWS. Presented from Parramatta (EB.1.32), accessible from Campbelltown (26.1.50) and Penrith (Y239).

Abstract: It is extremely useful to have right information at the right time. Social Life Networks (SLN) extend the capabilities of current social networks by combining them with the technological advances now found in Smartphones that include myriad of sensors and multimedia input and output capabilities to provide essential information to support livelihood activities. The challenge is to provide this information within the required context. For this we need to model the context by acquiring the physical data to provide meaningful abstractions with respect to the application domain and the needs of the users. We have developed a physical context model based on user profile, location, time and activity and a mapping to match the logical context of various data sources from which we can get the required information. Based on this model we have developed a SLN for farmers in Sri Lanka to provide agricultural information in the context of farming life cycle stages, location of their farm land, cultivation season and other economic parameters. In the field trails there was unanimous agreement among farmers that this application is very useful for them because they were able to get the required information in context.

Biography: Maneesh Mathai is a Master of Science (Honours) student in the School of Computing, Engineering and Mathematics, at the University of Western Sydney. He graduated from Mahatma Gandhi University, India, specializing in computer science in 2008. Previously, he worked as a Web developer, working closely with NGOs to develop an online platform that enables the print-impaired people to connect and share accessible content as well as build conversations and communities around the shared content. In addition, he has worked with medical practitioners to develop an online collaborative platform for the medical community to share multimedia contents. In his Masters research project he aims to identifying a computational models for context analysis and approaches for content aggregation. His research interests include Social Life Networking, Content Management Systems, Scenario analysis and Modelling information systems.