Ontology-based multilingual search in recommendation systems

Abstract

The information on the web is not only published by an original language, but also expressed in many different languages. Almost recommendation systems also lack mechanisms to support users overcoming the language problem. In these systems, it is difficult to search a specific value (e.g., movie artist, movie title in movie domain) by using native language. In this paper, we present our approach to deal with this problem. We develop an ontology-based multilingual recommendation system using integrated data from Linked Open Data to support user with in different languages on movie domain. Multilingual Movie Recommendation System (MMRS) for searching as a case of study is developed. In this system, we illustrate a more comfortable and flexible implementation.