Portal de Periódicos da CAPES

Ontology-Based Recommender System for Sport Events

2019; Springer Nature; Linguagem: Inglês

10.1007/978-3-030-19063-7_69

2194-5357

Quang Dang Nguyen, Luan N. T. Huynh, Tuyen P. Le, TaeChoong Chung,

Video Analysis and Summarization

Sport event participation has changed much recently with effective support of technology. Advanced developments in recommender systems and World Wide Web bring chances such as efficiently distantly booking to alone travelers which allows them to enjoy sport events without being dependent on expensive tourist agencies as in the past. However, currently, popular information sources for such a recommender system are isolated and mainly relied on Web 2.0 formats which are difficult to stored and processed, especially among different platforms and communities. To utilize huge resources of Web 2.0 as well as apply cutting-edge features of Web 3.0 and under-developing Web 4.0, the authors propose an implementation of a hybrid system which collects data from different sources in the Internet (Mashup), apply machine learning to process raw information (Natural Language Processing and Unsupervised Clustering), add semantics to the processed data and make it compatible to latest web generation (Ontology), and provide recommendations based on smart content-based filtering and social-network-based user profiles for sport events. Empirical results show promising applications of such a framework to the market portion of alone travelers and also set an example as a demonstration for the authors' expectation toward Web 4.0 applications in the future.