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Special Issue on Information Science and Technology



This special issue presents innovative knowledge and advances in Information Science and Technology. Its objectives are to facilitate and support research related to information science and the applications. The issue brings revised and significantly extended versions of six papers presented and selected at The 9th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2014). APIC-IST 2014, organized by KSII (Korean Society for Internet Information) was the 9th International Conference having targeted objectives to gather researchers and practitioners from academia and industry to share leading-edge knowledge and ideas in Internet Computing and related areas. APIC-IST 2014 was hosted in Kathmandu, the capital and largest urban agglomerate of Nepal on July 14-18, 2014.

The work by Mikyoung Lee et al. entitled “On a Hadoop-based Analytics Service System has discussed the development of an analysis service that uses Hadoop for improving the performance of a database management system (DBMS)-based analysis service system that processes big data.

In the article by Jangwon Gim et al. titled “Incremental Discriminating Method for Acronyms in Heterogeneous Resources ”, an incremental discriminating method is proposed to discriminate acronyms and their full names or expansions in scientific and technical literature abstracts by learning Wikipedia definition statements. And through experiments it has been proved that a noun phrase (NP)-type feature has better performance than a noun (NN) type feature in terms of precision rate.

Sungbum Park et al, the authors of the paper entitled “A Selection Method of Database System in Big Data Environment: A Case Study From Smart Education Service in Korea” has suggested an optimal combination of the database system to demonstrate polyglot persistence concept from the example of the smart education service in Korea.

The article by Frank Elijorde et al. entitled “Attaining Reliability and Energy Efficiency in Cloud Data Centers Through Workload Profiling and SLA-Aware VM Assignment” has proposed a resource provisioning technique which involves clustering of similar VMs in a cloud datacenter based on their workload profile. The authors then combined it with an SLA-aware approach for VM assignment in order to improve the efficiency of virtual resource provisioning to increase the quality of service.

The paper entitled “The Feature Selection Method based on Genetic Algorithm for Efficient of Text Clustering and Text Classification” by Myung-Mook Han et al. has engrossed on the area of big data text mining and has designed a new Generic Algorithm (GA) algorithm that focuses on selecting a set of optimized features from the corpus. The authors then conducted clustering experiments on a set of spam-mail documents in order to verify and to improve feature selection performance, and then claimed better performance of FSGA algorithm of Text Clustering and Classification.

The next article entitled “Development of a DVB-x2 Broadcast Gateway with Common Modulator Interface” is by the authors Jeongwook Seo et al. in the area of Digital Video Broadcasting. The authors designed it for all the DVB-x2 services such as DVB-T2 for terrestrial, DVB-C2 for cable, and DVB-S2 for satellite and claimed better performance in the buffer usage by about 24%, compared to the use of separate DVB-T2/C2/S2 buffers

Guest Editors:
Dr. Junchul Chun
Kyonggi University, Korea

Dr. Seung Ryul Jeong
Dankook University, Korea