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Abstract-Ontology is a concept to organize domains that can be widely used in many fields. For building the OWL ontology, several existing data sources such as XML, relational databases were used. Most researchers try to map data in a format of relational database into the OWL ontology using OWL syntax, which sometimes is difficult, especially for a person who does not know this syntax, or uses mistaken work to create the OWL ontology. So, in this research, we propose a mechanism to construct OWL ontology in order to reduce the problem of lack of understanding about the OWL ontology syntax based on Entity Relationship Model (ER), which is a model for describing data in a conceptual level of database design. We demonstrate a step-by-step transformation of ER model into OWL ontology using a tool editor called Proté gé . The evaluations of the building ontology will use FaCT++ and HermiT 1.3.8. The results have shown that the ability to convert each part of ER model is very accurate, fast and easy to use. Index Terms-ER model, OWL ontology, Proté gé editor. I. INTRODUCTIONOntologies [1] play an important role in semantic description for common understanding and classification of the documents in the knowledge domain [2]. They use a single concept for reducing ambiguous concepts or terminology and support the exchange of information retrieval; they are also critical to the development of the knowledge based systems. Therefore, the knowledge base of ontologies can be exchanged or reused and published for others to be used widely in various fields. These Ontologies are being applied in many applications such as Artificial Intelligence, E-Commerce, Knowledge Management, Information Retrieval, Semantic Web and Recommendation System.The language used to describe ontologies will be depending on the format of this language. The popular pattern is a form that is used for describing resources on the web and in the human form easily understood such as RDFS and OWL. At present, most of the ontologies are constructed manually and use several existing data sources [3] such as XML, relational databases and web pages etc.A majority of this research has been done on building ontologies using relational database. The uses of this OWL syntax are commonly found in many researches. They have tried to construct OWL ontologies by mapping several data Manuscript received December 13, 2014; revised March 20, 2014. This work was supported in part by grant from Suranaree University of Technology through the funding of Data Engineering Research Unit.The authors are with the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand (e-mail: pasapitchchujai@gmail.com).source into OWL syntax. The source of these data most often comes from relational database, which can be found in the following research:Upadhyaya and Kumar [4] proposed an approach of automatic mapping Extended E/R diagram into OWL by developing the prototype of ERONTO using Java and Jena 2.1. Igor and Marguerite [5] proposed an approac...

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Lately, recommendation system has an important role in providing advice on products and services to match the various requirements of users. The popular method for developing recommender system is Collaborative Filtering. This method will search for other users in the systems that are interested by the same or similar items. With this method, users need not to know each other. The system will then suggest choices of other users that might be interested by the current user.However this technique is not work well with scarce data. This problem is known as the sparsity problem. Therefore, we propose to modify Collaborative Filtering using frequent itemsets by imputing the missing value. According to experimental results, the proposed method can properly fill up the missing values and improve the accuracy of recommendations to users with MAE of 0.55 with the neighborhood size of 30.

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