• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.98-99
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• 2004

• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.291-300
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• 2010

Group-based learning is known to be an effective means to improve scholastic achievement in online learning. Therefore, there are some previous researches for the group-based learning. A lot of previous researches define factors for grouping from the characteristics of classes, teacher's decision and students' preferences and then generate a group based on the defined factors. However, many algorithms proposed by previous researches depend on a specific class and is not a general approach since there exist several differences in terms of the need of courses, learners, and teachers. Moreover it is hard to find a automatic system for group generation. This paper proposes a grouping system which automatically generate a learner group according to characteristics of various classes. the proposed system automatically generates a learner group by using basic information for a class or additional factors inputted from a user. The proposed system defines a set of rules for learner grouping which enables automatic selection of a learner grouping algorithm tailored to the characteristics of a given class. This rule based approach allows the proposed system to accommodate various learner grouping algorithms for a later use. Also we show the usability of our system by serviceability evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1A
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• pp.16-23
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• 2008

In this paper, we propose a new code grouping interference cancellation(IC) receiver for multirate wideband code division multiple access(WCDMA) system based on orthogonal variable spreading factor(OVSF) code. The users are assigned different lengths of OVSF codes as a spreading code according to their data rates and divide the active users having same representative code split into a group for effective cancellation. The code grouping IC receiver performs cancellation between the groups first and cancellation within group. This proposed IC receiver can cancel the interferences using desired user's code information and then desired signals are detected. The results show that the large improvement in performance can be attained by groupwise IC scheme and we can make the effective systems compare to conventional ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.157-176
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• 2011

An interest-based P2P constructs the peer connections based on similarities for efficient search of resources. A clustering technique using peer similarities as data is an effective approach to group the most relevant peers. However, the separation of groups produced from clustering lowers the scalability of a P2P network. Moreover, the interest-based approach is only concerned with user-level grouping where topology-awareness on the physical network is not considered. This paper proposes an efficient scalable search for the interest-based P2P system. A scalable multi-ring (SMR) based on fuzzy clustering handles the grouping of relevant peers and the proposed scalable search utilizes the SMR for scalability of peer queries. In forming the multi-ring, a minimized route function is used to determine the shortest route to connect peers on the physical network. Performance evaluation showed that the SMR acquired an accurate peer grouping and improved the connectivity rate of the P2P network. Also, the proposed scalable search was efficient in finding more replicated files throughout the peer network compared to other traditional P2P approaches.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.117-128
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• 2004

Compared with traditional face-to-face instruction, online learning causes learners to experience more severe feeling of isolation and results in higher dropout rate. This is due to the lack of interaction, sense of belonging, membership, interdependency, cooperation among members and social environment that enables persistence in online learning. Therefore, it is very important for grouping e-learning community to lower the dropout rate and eliminate feeling of isolation. In this paper, the research has been done on the inclination test list to be applied for grouping the desirable learning community. And on the basis of this research, the grouping system for e-learning community(GSE) based on intelligent multi agents for an inclination test using homogeneous and heterogeneous items has been developed. GSE system has such properties that construct a personalized user profile by an agent, and then make groupings according to users' inclination. When this system was evaluated, about 88% of learners were satisfied, and they wanted the group not to be disorganized but to be maintained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2375-2382
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• 2011

The user clustering for web navigation pattern discovery is very useful to get preference and behavior pattern of users for web pages. In addition, the information by the user clustering is very essential for web personalization or customer grouping. In this paper, an algorithm for clustering the web navigation path of users is proposed and then some special navigation patterns can be recognized by the algorithm. The proposed algorithm has two clustering phases. In the first phase, all paths are classified into k-groups on the bases of the their similarities. The initial solution obtained in the first phase is not global optimum but it gives a good and feasible initial solution for the second phase. In the second phase, the first phase solution is improved by revising the k-means algorithm. In the revised K-means algorithm, grouping the paths is performed by the hyperplane instead of the distance between a path and a group center. Experimental results show that the proposed method is more efficient.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.493-500
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• 2008

Although modern day people gather many data from the network, the users want only the information needed. Using this technology, the users can extract on the data that satisfy the query. As the previous studies use the single data in the document, frequency of the data for example, it cannot be considered as the effective data clustering method. What is needed is the effective clustering technology that can process the electronic network documents such as the e-mail or XML that contain the tags of various formats. This paper describes the study of extracting the information from the user query based on the multi-attributes. It proposes a method of extracting the data such as the sender, text type, time limit syntax in the text, and title from the e-mail and using such data for filtering. It also describes the experiment to verify that the multi-attribute based clustering method is more accurate than the existing clustering methods using only the word frequency.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.115-125
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• 2005

This paper discusses how to effectively design a next-generation wireless communication system that can possibly provide very high data-rate transmissions and versatile quality services. In order to accommodate the sophisticated user requirements and diversified user environments of the next-generation systems, it should be designed to take an efficient and flexible structure for multiple access and resource allocation. In addition, the design should be optimized for cost-effective usage of resources and for efficient operation in a multi-cell environment. As orthogonal frequency division multiple access (OFDMA) has turned out in recent researches to be one of the most promising multiple access techniques that can possibly meet all those requirements through efficient radio spectrum utilization, we take OFDMA as the basic framework in the next-generation wireless communications system design. So, in this paper, we focus on introducing an OFDMA-based downlink system design that employs the techniques of hybrid multiple access (HMA) and frequency group (FG) in conjunction with intra-frequency group averaging (IFGA). The HMA technique combines various multiple access schemes on the basis of OFDMA system, adopting the multiple access scheme that best fits to the given user condition in terms of mobility, service, and environment. The FG concept and IFGA technique help to reduce the feedback overhead of OFDMA system and the other-cell interference (OCI) problem by grouping the sub-carriers based on coherence band-widths and by harmonizing the channel condition and OCI of the grouped sub-carriers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4372-4394
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• 2020

The distribution of popular videos incurs a large amount of traffic at the base stations (BS) of networks. Device-to-multi-device (D2MD) communication has emerged an efficient radio access technology for offloading BS traffic in recent years. However, traditional studies have focused on synchronous user requests whereas asynchronous user requests are more common. Hence, offloading BS traffic in case of asynchronous user requests while considering their time-varying characteristics and the quality of experience (QoE) of video request users (VRUs) is a pressing problem. This paper uses social stability (SS) and video loading duration (VLD)-tolerant property to group VRUs and seed users (SUs) to offload BS traffic. We define the average amount of data transmission (AADT) to measure the network's capacity for offloading BS traffic. Based on this, we formulate a time-varying bipartite graph matching optimization problem. We decouple the problem into two subproblems which can be solved separately in terms of time and space. Then, we propose the socially aware D2MD user selection (SA-D2MD-S) algorithm based on finite horizon optimal stopping theory, and propose the SA-D2MD user matching (SA-D2MD-M) algorithm to solve the two subproblems. The results of simulations show that our algorithms outperform prevalent algorithms.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.322-325
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• 2000

In a batch scheduling policy being different from real video system, the requests are not served immediately due to grouping user's requests upon every scheduling points. Such waiting delays by inefficient managements makes an unfair service to users and increases the possibility of higher reneging rates. This paper proposes an adaptive batch scheduling scheme which reduces the average waiting time of user’s requests and reduces the starvation problem for requesters of less popular movies. The proposed scheme selects dynamically multiple videos in given intervals based on the service patterns which reflect the popularity distribution and resource utilizations. Experimental simulation shows that proposed scheme improves about 20-30 percent of average waiting time and reduces significantly the starving requesters comparing with those of conventional methods such as FCFS and MQL.