An Effective Cold Start Recommendaton Method Using A Web Of Trust

摘要: Cold start recommendations are important because they help build user loyalty, which is the key to success of e-services and e-commerce systems. Recommending useful information for new users generally creates a sense belonging encourages them visit systems frequently. However, as take time become familiar with recommendation systems, usually have limited about newcomers difficulty providing appropriate recommendations. The cold phenomenon has serious impact on performance To address problem, we propose method that integrates web trust model identify trustworthy users. suggestions those then aggregated provide Experiments based well-known Epinions dataset demonstrate proposed effective efficient, outperforms methods by significant margin.