Extending Recommender System by Incorporating Semantic-social Information

Khaled Sellami ； Rabah Kassa ； Pierre F. Tiako

《Research Journal of Applied Sciences, Engineering and Technology》 11卷7期 (2015/11) Pp. 674-684

並列摘要

Recommender systems in e-commerce applications have become business relevant in filtering the vast range of information available in web shop (and the internet) to present useful recommendation to user. In this study we combine social network analysis and semantic user profile to provide a new semantic-social recommendation, featuring a two-stage process that relies on a simple formalization of semantic user preferences that contains the user's main interests and heuristically explores the social graph. Given a recommendation request concerning a product, the semantic-social recommendation algorithm compares the user preferences, which are found in the exploration path, with the product preferences by referencing them to domain ontology. Experiments on real-world data from Amazon, examine the quality of our recommendation method as well as the efficiency of our recommendation algorithms.

並列關鍵字

Recommender systems ； semantic web ； social network ； taxonomy ； user preferences