Context Based Content Aggregation For Social Life Network

Better decisions can be made in the profession of the users if they can filter out the relevant information from all the available information sources. The mass availability of the mobile devices has enabled the users to quickly access timely information from any location. The aim of this work is to identify a suitable way to provide timely information in context by capturing contextual information through the mobile device, to support the activities of the user. The context model tries to identify the context of the user by identifying the task being performed by the user. The system is aware of the information need and the information source for each task of the user and the relevant information is filtered out of the information source, by using the users context. The context model was designed and tested for the farming domain, to support the livelihood activities of the farmer, by extending the concepts of Social Life Networks. Social Life Networks aggregates information from various sensors on a mobile phone, other published data sources and micro blogs such as Twitter to detect evolving situations and make that information available to the users in real time. This initial prototype was evaluated with a sample of farmers to check usefulness of provided information and usability of the application in order to support their day to day decision making process. The sample group strongly endorsed the various aspects of the proto-type application and provided valuable insights for improvement. The current application is a specific instance of the SLN project and we plan to create more application for SLN to test and refine the context models.