I-hsien Ting

National University of Kaohsiung, Department of Information Management, Faculty Member

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Dr. Derrick I-Hsien Ting, who is now an Associate Professor in Department of Information Management, National University of Kaohsiung, Taiwan. He is now also taking the position of Chair of Department of Information Management, NUK.He received Ph.D. in Computer Science from The University of York, UK and received MBA in Information Management from National Changhua University of Education, Taiwan. He received BBA in Business Administration from Chinese Culture University, Taiwan.His research interests are mainly on Artificial Intelligence, Social Network, Web and Data Mining, Web Intelligence, Knowledge Management, E-commerce, Recommender System, Big and Open Data, Machine Learning.
Phone: +88675919751
Address: No. 700, Kaohsiung University Road, Kaohsiung City, 811, TAIWAN

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Multidisciplinary Social Networks Research

Communications in Computer and Information Science, 2014

The rise of Social Networking Services (SNSs) has not only transformed people as well as consumer... more The rise of Social Networking Services (SNSs) has not only transformed people as well as consumer behavior on the Internet, but also transformed the means by which various enterprises globally conduct their promotional and marketing campaigns. There are a variety of means by which enterprises have launched their marketing campaigns on Social Networking Services, and one of the most common techniques adopted is through extensive advertising campaigns on SNSs. This study seeks to examine consumer behaviors towards advertisements on Social Networking Services. Key factors affecting consumer behaviors include usage pattern, the credibility of a particular Social Networking Service as well as electronic word-of-mouth. This clearly illustrates that in today’s virtual electronic world, social media have progressed from being merely a place to meet people, to being a virtual sales floor. It is unexpected that consumer behaviors are influenced by the electronic word-of-mouth of friends rather than that of strangers.

K-anonymous path privacy on social graphs

Journal of Intelligent & Fuzzy Systems, 2014

Growing popularity of social networking not only brings the convenience of information sharing bu... more Growing popularity of social networking not only brings the convenience of information sharing but also concerns of privacy breaches. Information on social networks can be modeled as un-weighted or weighted graph data. To preserve privacy, k-anonymity on relational, set-valued, and graph data have been studied extensively in recent years. In this work, we consider the edge weight anonymity problem. In particular, to protect the weight privacy of the shortest path between two vertices on a weighted graph, we present a new concept called k-anonymous path privacy. A published social network graph with k-anonymous path privacy has at least k indistinguishable shortest paths between the source and destination vertices. Three greedy-based modification algorithms, based on modifying different types of edges, to achieve k-anonymous path privacy are proposed. Experimental results showing the feasibility and characteristics of the proposed approach are presented. The proposed techniques clearly provide different options to achieve the same level of privacy under different requirements.

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