Learn More
0957-4174/$ see front matter 2011 Elsevier Ltd. A doi:10.1016/j.eswa.2011.01.048 ⇑ Corresponding author. Tel.: +1 613 562 5800x624 E-mail address: hnkim@mcrlab.uottawa.ca (H.-N. With the popularity of social media services, the sheer amount of content is increasing exponentially on the Social Web that leads to attract considerable attention to recommender(More)
This paper proposes a collaborative filtering method with usercreated tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users’ preferences for items. In addition, we explore several advantages of collaborative tagging for future searching and information sharing which(More)
Recommender systems, which have emerged in response to the problem of information overload, provide users with recommendations of content suited to their needs. To provide proper recommendations to users, personalized recommender systems require accurate user models of characteristics, preferences and needs. In this study, we propose a collaborative(More)
In the fields of production, manufacturing and supply chain management, Radio Frequency Identification (RFID) is regarded as one of the most important technologies. Nowadays, Mobile RFID, which is often installed in carts or forklift trucks, is increasingly being applied to the search for and checkout of items in warehouses, supermarkets, libraries and(More)