A Context-Aware Recommender System Using Ontology Based Approach for Travel Applications
Preeti R. Dodwad1, L. M. R. J. Lobo2

1Miss. Preeti R. Dodwad, M.E.(CSE) Student in Department of Computer Science and Engineering , Walchand Institute of Technology, Solapur, India.
2Mr. L. M. R. J. Lobo, Assoc. Prof., in Department of Computer Science and Engineering , Walchand Institute of Technology, Solapur, India.
Manuscript received on September 10, 2014. | Revised Manuscript Received on September 12, 2014. | Manuscript published on September 18, 2014. | PP: 08-12 | Volume-1 Issue-10, September 2014.
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: the purpose of tourism is to travel for relaxation and enjoyment. However, when tourists use internet to search for data about travel spots, events and relevant services they experience a data overload. It is also difficult for them to select what is truly interesting from sheer amount of available information. For a tourist guide system, it is still a tough task to provide proper travel information for tourists who posses different personal interests. Therefore, our aim is to develop a recommender system which considers tourists’ personal interests and related context, so that tourists can get relevant travel information with least amount of effort. This recommender system uses an ontology based approach. Ontology consists of a set of concepts relevant to a specific domain and the relationships between them. Such an ontology structure can reason depending on the choices of a user. The user profile keeps the degrees of interest of the user on many concepts by making use of a membership function. Each concept of ontology is a fuzzy set and any user can fit into this fuzzy set to a definite degree. When preliminary assignment of user choices is done, we performed an upward and downward propagation of user’s interest degrees which utilizes the taxonomical information of the ontology. The information about the user’s choices is propagated throughout the complete set of concepts. This developed system has been successfully applied for a Tourism scenario and is based on user context. This system is built on an Android platform and has generated successful results.
Keywords: Context-aware recommendations, user interests, ontology, recommender systems.