Heung-Nam Kim

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Outline Introduction Related Work Cooperative Diversity MAC Performance Conclusion Introduction In wireless ad hoc networks, signal fading and interference are two major obstacles in realizing their full potential in delivering signals. Cooperation among the nodes is considered critically important in addressing these problems. Introduction Diversity(More)
As mobile devices require more computation as well as communication activities, energy efficiency of a processor becomes the most critical because a processor contributes to a major part of total energy consumption. A number of research efforts have been devoted to reduce energy consumption of a processor without impacting the performance through the use of(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 recommender systems, social networks are considered as a trusted source for user interests. In addition, user context can enhance users' decision making. In this paper, we design a new architecture for user personalization which combines both social network data and context data. Our system aggregates a user's preference data from various social(More)
We propose a semantic collaborative filtering method to enhance recommendation quality derived from user-generated tags. Social tagging is employed as an approach in order to grasp and filter users’ preferences for items. In addition, we explore several advantages of semantic tagging for ambiguity, synonymy, and semantic interoperability, which are notable(More)