• Title/Summary/Keyword: Business Rule

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A study on asset management investment strategy model by trade probability control on futures market (선물시장에서 거래확률 조정을 통한 자산운용 투자전략 모델에 관한 연구)

  • Lee, Suk-Jun;Kim, Ji-Hyun;Jeong, Suk-Jae
    • Management & Information Systems Review
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    • v.31 no.3
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    • pp.21-46
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    • 2012
  • This paper attempts to offer an effective strategy of hedge fund based on trade probability control in the futures market. By using various technical indicators, we create an association rule and transforms it into a trading rule to be used as an investment strategy. Association rules are made by the combination of various technical indicators and the range of individual indicator value. Adjustments of trade probabilities are performed by depending on the rule combinations and it can be utilized to establish an effective investment strategy onto the risk management. In order to demonstrate the superiority of the investment strategy proposed, we analyzed a profitability using the futures index based on KOSPI200. Experiments results show that our proposed strategy could effectively manage and response the dynamics investment risks.

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Real-time Scheduling of Scrap Disposal using Multi-Pass Simulation in Steel Industry (Multi-Pass 시뮬레이션을 이용한 제철소 구내의 스크랩 운송 실시간 스케줄링)

  • Lee, Tae-Ha;Park, Sung-Sik;Cho, Hyun-Bo
    • IE interfaces
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    • v.11 no.1
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    • pp.119-129
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    • 1998
  • The relative importance of Logistics in steelworks industry is rather higher among other business activities. The objective of the paper is to propose the methodology for real-time vehicle scheduling for scrap disposal in the steelworks industry. Currently, the rule necessary to assign vehicles to a specific job is strictly fixed. The paper adopts the multi-pass rule selector (MPRS) that suggests a promising rule used for vehicle dispatching for a period of time. The MPRS is regularly invoked if necessary and then evaluates a set of rule candidates to select the best rule with respect to the system performance criteria. The experiment shows that the proposed approach outperforms the current single-pass strategy.

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Country-Level Governance Quality and Stock Market Performance of GCC Countries

  • MODUGU, Kennedy Prince;DEMPERE, Juan
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.8
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    • pp.185-195
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    • 2020
  • This study examines the association between governance quality at country level and stock market performance. Specifically, the study investigates the influence of control of corruption, government effectiveness, political stability and absence of violence, rule of law, regulatory quality, and voice and accountability on all-share index of the stock markets of the six Gulf Cooperation Council (GCC) countries. This study is anchored on two theories - the Efficient Market Hypothesis (EMH) and Institutional Theory. The study employs panel data spanning from 2006 to 2017. The findings show that political stability and absence of violence and rule of law exhibit a significant positive impact on stock market performance, while regulatory quality and voice and accountability have a significant, but negative relationship with stock market performance. The results imply that quality of governance in terms of rule of law and political stability devoid of violence have strong impact on stock market returns. Similarly, improved stock market returns are largely dependent on the efficiency of the institutional environment of market as investors are always wary of the inherent risks associated with the uncertainty of the market. This study has crucial policy implications for the government of the GCC countries and stock market participants.

Electronic Commerce Using on Case & Rule Based Reasoning Agent (전자상거래를 위한 규칙 및 사례기반 추론 에이전트)

  • 박진희;허철회;정환묵
    • The Journal of Society for e-Business Studies
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    • v.8 no.1
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    • pp.55-70
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    • 2003
  • With the gradual growth of the electronic commerce various forms of shopping malls are constructed, and their searching methods and function are studied many ways. However, the recent outcome is still inadequate to search for goods for the tastes and demands of customers. To construct the shopping mall on the electronic commerce and help customers with purchasing goods, the efficient interface for the customers to contact the shopping malls should be founded and the customers should be able to search the goods they want. Therefore, in this paper, we designed the Intelligent Integration Agent System (IIAS) using the multi-agent formed by the integration agent which integrates the case based reasoning(CBR) and the rule based reasoning(RBR) and the user agent which manages users' profiles. IIAS performs the rule based reasoning on the subject issue first, then provides the unsatisfying search results from the rule-base reasoning to the customers through the user agent, which enables the search of the goods most similar to the ones that meet the tastes and demands of the customers. That is, the accuracy and the speed has been improved by reasoning with the similarity adjustable integration agent which can pick out the goods of customers wants by modifying the weights of properties according to those of the customers.

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A Study on the Development of Internet Purchase Support Systems Based on Data Mining and Case-Based Reasoning (데이터마이닝과 사례기반추론 기법에 기반한 인터넷 구매지원 시스템 구축에 관한 연구)

  • 김진성
    • Journal of the Korean Operations Research and Management Science Society
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    • v.28 no.3
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    • pp.135-148
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    • 2003
  • In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.

Rule based Component Development Technique and Case study (룰 기반 컴포넌트 개발 기법 및 사례)

  • Kim Jeong Ah;Hwang Sun Myung;Jin Young Taek
    • The KIPS Transactions:PartD
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    • v.12D no.2 s.98
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    • pp.275-282
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    • 2005
  • In order to increase extendibility and reusability of components during component design, the variability discovered in a business application development needs to be defined to separate rules. That is because component adaptation techniques through redefinition of implementation classes and interface wrapping have limits to support the component reusability. Therefore, It's essential to design the component which takes into account the future reusability in the component development. In this paper, we extended the existing component architecture to incorporate rule components by separating variable properties from the components and defined the necessary syntax for the rule definition. In the case study, we built the business components for an insurance sales application and verified the component reusability through the rule redefining.

Over the Rainbow: How to Fly over with ChatGPT in Tourism

  • Taekyung Kim
    • Journal of Smart Tourism
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    • v.3 no.1
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    • pp.41-47
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    • 2023
  • Tourism and hospitality have encountered significant changes in recent years as a result of the rapid development of information technology (IT). Customers now expect more expedient services and customized travel experiences, which has intensified competition among service providers. To meet these demands, businesses have adopted sophisticated IT applications such as ChatGPT, which enables real-time interaction with consumers and provides recommendations based on their preferences. This paper focuses on the AI support-prompt middleware system, which functions as a mediator between generative AI and human users, and discusses two operational rules associated with it. The first rule is the Information Processing Rule, which requires the middleware system to determine appropriate responses based on the context of the conversation using techniques for natural language processing. The second rule is the Information Presentation Rule, which requires the middleware system to choose an appropriate language style and conversational attitude based on the gravity of the topic or the conversational context. These rules are essential for guaranteeing that the middleware system can fathom user intent and respond appropriately in various conversational contexts. This study contributes to the planning and analysis of service design by deriving design rules for middleware systems to incorporate artificial intelligence into tourism services. By comprehending the operation of AI support-prompt middleware systems, service providers can design more effective and efficient AI-driven tourism services, thereby improving the customer experience and obtaining a market advantage.

A Study on The Effectiveness of Tax Assistance System (조세지원체계의 유효성에 관한 연구)

  • Kim, Young-Il;Lee, Eun-Ha
    • Korean Business Review
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    • v.13
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    • pp.159-178
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    • 2000
  • Tax assistance system in Korea is a one that is designed by the central government to achieve specific policy objectives through the tax relief for economic activities or specific industries, leading to the development of the industries, Thus, the purpose of this study is to see if the government's direct tax assistance system for small and medium manufacturing firms is effective and then to contribute to establishing necessary policies for an effective tax assistance system based on the identification of a direct assistance system that is substantially useful to those firms. T- test was performed to see if there was a difference in tax burden between small and medium manufacturing firms and small and medium non-manufacturing firms and also to see whether the direct assistance system was effective. The results obtained from the statistical analyses are as follows: (1) The tax reduction rule applied to small and medium firms was turned out to be effective based on the fact that the effective tax rates of the small and medium firms to which the rule was applied were, on the average, significantly lower than those of the Listing large corporation which did not receive the tax benefit and also on the fact that the tax savings rates of the small and medium firms which could apply the rule were, on the average, significantly higher than those of the Listing large corporation to which the rule was not applied. (2) The tax credit rule applied to small and medium manufacturing firms was also turned out effective based on the same fact as described in the case of the application of the tax reduction rule.

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A Post-Analysis of Decision Tree to Detect the Change of Customer Behavior on Internet Shopping Mall

  • Kim, Jae kyeong;Song, Hee-Seok;Kim, Tae-Sung
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.456-463
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    • 2001
  • Understanding and adapting to changes of customer behavior in internet shopping mall is an important aspect to survive in continuously changing environment. This paper develops a methodology based on decision tree algorithms to detect changes of customer behavior automatically from customer profiles and sales data at different time snapshots. We first define three types of changes as emerging pattern, unexpected change and the added/perished rule. Then, it is developed similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is developed to evaluate the amount of change. A Korean internet shopping mall case is evaluated to represent the performance of our methodology. And practical business implications for this methodology are also provided.

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Odoo Data Mining Module Using Market Basket Analysis

  • Yulia, Yulia;Budhi, Gregorius Satia;Hendratha, Stefani Natalia
    • Journal of information and communication convergence engineering
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    • v.16 no.1
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    • pp.52-59
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    • 2018
  • Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.