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Journal of Intelligence and Information Systems,
Vol. 13, No. 4, December 2007
Classification of the Architectures of Web based Expert Systems
Gyoo Gun Lim
Vol. 13, No. 4, Page: 1 ~ 16
Keywords : Web-Based Expert System, Expert System, Model, Framework, Classification
Abstract
According to the expansion of the Internet use and the utilization of e-business, there are an increasing number of studies of intelligent-based systems for the preparation of ubiquitous environment. In addition, expert systems have been developed from Stand Alone types to web-based Client-Server types, which are now used in various Internet environments. In this paper, we investigated the environment of development for web-based expert systems, we classified and analyzed them according to type, and suggested general typical models of web-based expert systems and their architectures. We classified the web-based expert systems with two perspectives. First, we classified them into the Server Oriented model and Client Oriented model based on the Load Balancing aspect between client and server. Second, based on the degree of knowledge and inference-sharing, we classified them into the No Sharing model, Server Sharing model, Client Sharing model and Client-Server Sharing model. By combining them we derived eight types of web-based expert systems. We also analyzed the location problems of Knowledge Bases, Fact Bases, and Inference Engines on the Internet, and analyzed the pros & cons, the technologies, the considerations, and the service types for each model. With the framework proposed from this study, we can develop more efficient expert systems in future environments.
Rethinking of Self-Organizing Maps for Market Segmentation in Customer Relationship Management
Jounghae Bang
Vol. 13, No. 4, Page: 17 ~ 34
Keywords : CRM, Market Segmentation, Self-Organizing Maps, Clustering, Online-Marketing
Abstract
Organizations have realized the importance of CRM. To obtain the maximum possible lifetime value from a customer base, it is critical that customer data is analyzed to understand patterns of customer response. As customer databases assume gigantic proportions due to Internet and e-commerce activity, data-mining-based market segmentation becomes crucial for understanding customers. Here we raise a question and some issues of using single SOM approach for clustering while proposing multiple self-organizing maps approach. This methodology exploits additional themes on the attributes that characterize customers in a typical CRM system. Since this additional theme is usually ignored by traditional market segmentation techniques we here suggest careful application of SOM for market segmentation.
Machine-printed Numeral Recognition using Weighted Template Matching with Chain Code Trimming
Minchul Jung
Vol. 13, No. 4, Page: 35 ~ 44
Keywords : Template Matching, Numeral Recognition, Chain Code
Abstract
This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.
A Store Recommendation Procedure in Ubiquitous Market
Jae Kyeong Kim, KyungHee Chae, and Min Yong Kim
Vol. 13, No. 4, Page: 45 ~ 63
Keywords : Ubiquitous Computing, Ubiquitous Market, Store Recommender System, Apriori Algorithms
Abstract
Recently as ubiquitous environment comes to the fore, information density is raised and enterprise is being able to capture and utilize customer-related information at the same time when the customer purchases a product. In this environment, a need for the recommender systems which can deliver proper information to the customer at the right time and right situation is highly increased. Therefore, the research on recommender systems continued actively in a variety of fields. Until now, most of recommender systems deal with item recommendation. However, in the market in ubiquitous environment where the same item can be purchased at several stores, it is highly desirable to recommend store to the customer based on his/her contextual situation and preference such as store location, store atmosphere, product quality and price, etc. In this line of research, we proposed the store recommender system using customer's contextual situation and preference in the market in ubiquitous environment. This system is based on collaborative filtering and Apriori algorithms. It will be able to provide customer-centric service to the customer, enhance shopping experiences and contribute in revitalizing market in the long term.
Performance Improvement of a Movie Recommendation System using Genre-wise Collaborative Filtering
Jae Sik Lee, and Seog Du Park
Vol. 13, No. 4, Page: 65 ~ 78
Keywords : Template Matching, Numeral Recognition, Chain Code
Abstract
This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.
Statistical Image Quality Measure
Kyoung yul Bae
Vol. 13, No. 4, Page: 79 ~ 90
Keywords : Image Quality Measure, Statistical Image Quality Measure, Human Visual System Segments and the Image Qulities
Abstract
he image quality measure is an important issue in the image processing. Several methods which measure the image quality have been proposed and these are based on the mathematical point of view. However, there is difference between the mathematicalmeasure and the measure based on the human visual system and a new measure has to be proposed because the final target of the image is a human visual system In this paper, a statistical image quality measure which is considered the human visual feature was suggested. The human visual system is using the global quality of the image and the local quality of the image and the local quality is more important to human visual system. In this paper, the image divided into several segments and the image qualities were calculated respectively. After then, the statistical method using scoring was applied to the image qualities. The result of the image quality measure was similar to the result of measure based on the human visual system.
Adaptive Ontology Matching Methodology for an Application Area
Wooju Kim, Sung Jun Ahn, Juyoung Kang, and Sangun Park
Vol. 13, No. 4, Page: 91 ~ 104
Keywords : Semantic Web, Ontology Matching, Ontology
Abstract
Ontology matching technique is one of the most important techniques in the Semantic Web as well as in other areas. Ontology matching algorithm takes two ontologies as input, and finds out the matching relations between the two ontologies by using some parameters in the matching process. Ontology matching is very useful in various areas such as the integration of large-scale ontologies, the implementation of intelligent unified search, and the share of domain knowledge for various applications. In general cases, the performance of ontology matching is estimated by measuring the matching results such as precision and recall regardless of the requirements that came from the matching environment. Therefore, most research focuses on controlling parameters for the optimization of precision and recall separately. In this paper, we focused on the harmony of precision and recall rather than independent performance of each. The purpose of this paper is to propose a methodology that determines parameters for the desired ratio of precision and recall that is appropriate for the requirements of the matching environment.
An Empirical Study for Intelligence Level Measurement of Smart Home Appliances
Suhn Beom Kwon, Eunhong Kim , and Hwanbeom Lee
Vol. 13, No. 4, Page: 105 ~ 120
Keywords : Smart Home Appliances, Intelligence Level Measurement Model, Machine Intelligence Quotient
Abstract
The primary purpose of this study lies in developing an intelligence level measurement model which can be applied to information home appliances. To accomplish the study purpose, the literature on computer engineering and intelligence is comprehensively researched and critical elements necessary for measuring the intelligence of smart home appliances are extracted. Then an intelligence level measurement model is derived, and the model is validated by several academic and practical experts using Delphi technique. The measurement model developed in the study, on the one hand, can provide users with some objective standards to evaluate the intelligence level of smart home appliances. On the other hand, it can help home appliance product developers or related service providers decide the target intelligence level of the products or services more specifically. Consequently, the model can contribute to the revitalization of the smart home appliance industry as a whole.
Cost-Based Directed Scheduling : Part I, An Intra-Job Cost Propagation Algorithm
Jae Kyeong Kim, and Min Soo Suh
Vol. 13, No. 4, Page: 121 ~ 135
Keywords : Constraint Directed Scheduling, Cost Based Scheduling, Cost Propagation Algorithm
Abstract
Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.
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