Paper Title
Personalized Ontology Based Context Aware Recommender System

Modern Smartphone’s includes Context Aware applications that exploit knowledge about external operating conditions. They are equipped with various connectivity features and a wide range of sensors or hardware units that can be utilized as sensors such as accelerometers, GPS, light sensors, distance sensors, video/photo cameras, microphones. Android has become a popular mobile platform, which has addressed context-awareness from day one through hardware and software support for sensor and context management. Additionally, context reasoners and external Context Providers exist. Thus, it is possible that several context provider offer information of same type (e.g. location) but differ in quality levels (e.g. accuracy), representation (e.g. position in coordinates and as an address) and cost (e.g. battery consumption). Therefore support is required for selecting and activating ((de-) activation of local providers to save resources) one of the context providers. The proposed Personalized Context Aware Ontology based Recommendation System (PCARS); provide proactive services based on user’s usage pattern of mobile device combined with environmental context of user. This personalized service of user would capture location, user profile context. The framework searches the nearby locations and recommends the user with offers those best suits his/her profile. Ontological support is provided for common domain vocabularies, Knowledge sharing and Context reasoning. The essential part of the design phase of this framework would be representing concepts through Ontology by providing an unambiguous definition represented in the knowledge base of the system. It allows enriching information when it is imprecise or incomplete; it supports interoperability and exchange of information.