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Journal of Intelligence and Information Systems,
Vol. 15, No. 1, March 2009
The Bisection Seed Detection Heuristic for Solving the Capacitated Vehicle Routing Problem
Jun Taek Ko, Young Hoon Yu , and Geun Sik Jo
Vol. 15, No. 1, Page: 1 ~ 14
Keywords : Capacitated Vehicle Routing Problem, Bisection Seed Detection Heuristic, Sweep Algorithm, Exchange Algorithm, Exchange Algorithm
Abstract
The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.
Customer Model Analysis for UCC Knowledge Sharing Service : A Case
Eun Jung Yoon, and Kyoung Jun Lee
Vol. 15, No. 1, Page: 15 ~ 30
Keywords : UUCC, Technology Adoption in Life Cycle, Chasm, Customer Model, Business Model
Abstract
As knowledge is now being distributed and shared through the Internet not only in the form of text but also in that of video, UCC (User Created Content) knowledge video sharing services have emerged on the Internet such as Instructables.com. This paper deals with a UCC knowledge video service in real world and reports the case of analyzing its customer model. The knowledge video sharing service can be considered as both a kind of discontinuous innovation, which requires knowledge provider's technical ability of creating and editing UCC video, and a value network, which matches UCC providers and consumers therefore brings network effect, we first adopt the Chasm theory as the base of the customer model and refine the customer model referencing the Technographics, which is also an Internet-refinement of the Chasm model. Finally, non-customer analysis of Blue Ocean strategy is applied for exploring potential customers of the service.
A Recommendation Procedure based on Intelligent Collaboration between Agents in Ubiquitous Computing Environments
Jae Kyeong Kim, Hyea Kyeong Kim, and Il Young Choi
Vol. 15, No. 1, Page: 31 ~ 50
Keywords : Ubiquitous Computing, P2P, Collaboration Filtering
Abstract
As the collected information which is static or dynamic is infinite in ubiquitous computing environments, information overload and invasion of privacy have been pressing issues in the recommendation service. In this study, we propose a recommendation service procedure through P2P, The P2P helps customer to obtain effective and secure product information because of communication among customers who have the similar preference about the products without connection to server. To evaluate the performance of the proposed recommendation service, we utilized real transaction and product data of the Korean mobile company which service character images. We developed a prototype recommender system and demonstrated that the proposed recommendation service makes an effect on recommending product in the ubiquitous environments. We expect that the information overload and invasion of privacy will be solved by the proposed recommendation procedure in ubiquitous environment.
Robust Maneuvering Target Tracking Applying the Concept of Multiple Model Filter and the Fusion of Multi-Sensor
Deahwan Hyun, and HeeByung Yoon
Vol. 15, No. 1, Page: 51 ~ 64
Keywords : Maneuvering Target Tracking System, GPS, INS, Multiple Model Filter, Fusion Algorithm, Bayes Rule
Abstract
A location tracking sensor such as GPS, INS, Radar, and optical equipments is used in tracking Maneuvering Targets with a multi-sensor, and such systems are used to track, detect, and control UAV, guided missile, and spaceship. Until now, Most of the studies related to tracking Maneuvering Targets are on fusing multiple Radars, or adding a supplementary sensor to INS and GPS. However, A study is required to change the degree of application in fusions since the system property and error property are different from sensors. In this paper, we perform the error analysis of the sensor properties by adding a ground radar to GPS and INS for improving the tracking performance by multi-sensor fusion, and suggest the tracking algorithm that improves the precision and stability by changing the sensor probability of each sensor according to the error. For evaluation, we extract the altitude values in a simulation for the trajectory of UAV and apply the suggested algorithm to carry out the performance analysis. In this study, we change the weight of the evaluated values according to the degree of error between the navigation information of each sensor to improve the precision of navigation information, and made it possible to have a strong tracking which is not affected by external purposed environmental change and disturbance.
A Sophistication Framework for a Mother Company-Driven Global Manufacturing Network
Kwangho Park
Vol. 15, No. 1, Page: 65 ~ 85
Abstract
The main purpose of this paper is to propose a sophistication framework for a global manufacturing network (GMN) driven by a mother company to autonomously propagate and coordinate transaction data that are exchanged among manufacturing partners. The framework is based on conceptual fundamentals of previous research that provide a step toward ultimate successful collaboration in the supply chain and employs mobile agents for the coordination and propagation of transaction data. Maintaining the integrity of transaction data linked to a huge information web is difficult. With the sophistication functionalities of this framework, it becomes easy to effectively control the overall GMN operations and to accomplish the intended goals. The current level of sophistication focuses on the transaction data propagation. The sophistication level may be expanded up to business intelligence in the future.
Inferring and Visualizing Semantic Relationships in Web-based Social Network
Seung Hoon Lee, Ji Hyeok Kim , Heung Nam Kim , and Geun Sik Jo
Vol. 15, No. 1, Page: 87 ~ 102
Keywords : Virtual Community, Semantic Social Network, Social Ontolgy
Abstract
With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.
Conflict Pattern Analysis for Heterogeneous Workflow Interoperability Among Interorganizational Business Processes
Jin Soo Park, Boyoun Kim, and Yousub Hwang
Vol. 15, No. 1, Page: 103 ~ 122
Keywords : Workflow Management Systems, Interoperability, Business Process
Abstract
The recent development of information technology has been envisioned as the next technological wave and is expected to play an important role in diminishing boundaries between business organizations. Enterprises have recently resulted in a surge in workflow management, making business processes sharable among different business organizations. To make heterogeneous workflows operational, it is crucial that workflow management systems provide efficient tools for an environment supporting interoperability of business processes among different business organizations. As the potential of workflow management is becoming widely recognized, the demand for an integrated framework that facilitates interoperability among heterogeneous workflows is concomitantly growing. Despite the large body of work in the area of workflow management, few efforts are directed towards identifying conflict patterns for heterogeneous workflow interoperability of inter-organizational business processes. In this paper, we summarize state of the art research trends in workflow management research area and identify conflict patterns for heterogeneous workflows. We believe that this is one of the first attempts to conceptualize conflict patterns that exist on inter-organizational business processes. This paper opens up a novel avenue for workflow management research by supplementing the existing conceptual frameworks for workflow management.
Social Network : A Novel Approach to New Customer Recommendations
Jong Hak Park, Yoon Ho Cho , and Jae Kyeong Kim
Vol. 15, No. 1, Page: 123 ~ 140
Keywords : Social Network, New Customer Recommendation, Cold-Start Recommendation Problem, Collaborative Filtering
Abstract
Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.
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