• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• Korean Management Science Review
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• v.25 no.1
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• pp.1-9
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• 2008

This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.87-95
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• 2008

The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

• Journal of Korea Port Economic Association
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• v.33 no.4
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• pp.37-58
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• 2017

The implicit assumption of port selection studies based on survey and respondents' perceptions is that the preference of the port selection attributes is proportional to the selection behavior. Further, the straight lines of the port selection attributes could also have non-linear properties. This study confirms nonlinear characteristics of selection attributes by using Kano model. The findings of this study showed that several properties of carriers were evaluated as nonlinear characteristics, such as the intermodal links and network accessibility, and size of port and terminal. Hence, port service providers such as port authorities and terminal operating companiesl, should construct a port operation strategy that reflects the non-linear port selection characteristics of shipping companies. Since this study aimed at exploring the forms of port selection characteristics, long-term additional verification studies on ports and stakeholders at domestics and abroad were needed. The Kano model and importance-selection analysis method used for analysis and strategy establishment also need to be improved to capture evident characteristics and to present strategic guidelines.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.181-188
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• 2022

The purpose of this study is to identify selection attributes, functional benefits, psychological benefits, and values according to crossover shopping patterns (showrooming and webrooming). To achieve objectives of this study, a survey was designed based on the means-end chain theory, using the in-depth laddering technique and APT laddering technique which understanding the linkage of A(attributes)-FB(functional benefits)-PB(psychological benefit)-V(value). These two laddering techniques were used to construct a hierarchical value map (HVM) by linking selection attributes, functional benefits, psychological benefits, and value levels. The selection attribute items that showrooming shoppers consider important are 'price conformity', 'product information', 'product variety', and 'delivery service'. Functional benefit items were 'free purchase', 'economic benefit', 'communication', 'safety', and 'accurate Information', and psychological benefit items were 'convenience', 'relaxation', 'pleasure', 'rational consumption', and 'stability'. Finally, the value items were 'self-satisfaction', 'abundant life', 'achievement', 'happiness', and 'reasonable life'. Next, the selection attribute items that webrooming shoppers consider important are 'price conformity', 'product information', 'product variety', 'AS', 'shopping atmosphere', and 'seller service'. Functional benefit items were 'free purchase', 'economic profit', 'expression opinion', 'safety', and 'accurate information', and psychological benefit items were 'convenience', 'relaxation', 'rational consumption', and 'stability'. Finally, the value items were 'self-satisfaction', 'abundant life', 'happiness', and 'reasonable life'.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.414-423
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• 2008

The purpose of this article is identify the difference of selection attributes on super-deluxe hotel and economy hotel, which business travellers consider important and understand satisfaction with the results of it so as to seek the way for economy hotel to take superior competition differentiated from the super-deluxe hotel and towards world wide competitive level. And also it is to offer necessary basic concept for new investors or experienced investors who construct economy hotel. The results indicated that this article has an implication to offer basic data for the understand of a model of economy hotel and market segmentation for business travellers who want to the service of super-deluxe hotel level but prefer economy hotel which costs relatively inexpensive.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.135-140
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• 2007

Feature selection is a preprocessing technique commonly used on high dimensional data. Feature selection studies how to select a subset or list of attributes that are used to construct models describing data. Feature selection methods attempt to explore data's intrinsic properties by employing statistics or information theory. The recent developments have involved approaches like correlation method, dimensionality reduction and mutual information technique. This feature selection have become the focus of much research in areas of applications with massive and complex data sets. In this paper, we provide a feature selection method considering data characteristics and generalization capability. It provides a computational approach for feature selection based on fuzzy cluster analysis of its attribute values and its performance measures. And we apply it to the system for classifying computer virus and compared with heuristic method using the contrast concept. Experimental result shows the proposed approach can give a feature ranking, select the features, and improve the system performance.

• Asia pacific journal of information systems
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• v.12 no.1
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• pp.1-16
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• 2002

Most of searching systems used by shopping-mall provide too much information for user requirements or fail to provide appropriate items reflecting customer's preference. This paper aims to design and implement the product searching systems based on customer preference which will enable efficient product selection in the internet shopping-mall. The proposed system consists of user/provider interface, searching and model agent, data management system, and model management system. Especially, we construct the searching pattern database to support fast search using association mining method. And this system includes the customer-oriented decision model which shows the highly preferred products. Input weight value per attribute and preference level should be needed to compute priority grade of preference.