• Title/Summary/Keyword: Association Rules Analysis

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Identification of Authors and ethics of Research based on KODISA Case

  • ZHANG, Fan;SU, Shuai;YOUN, Myoung-KIl
    • Journal of Research and Publication Ethics
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    • v.1 no.2
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    • pp.11-13
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    • 2020
  • Purpose: The author wants to specify scope of research, identify without giving burden, prevent unfair identification of the author, admit of production of the outcome, enact rules of identification, and build up foundation of development. Also, this study defines scope of publication of outcome of research to prevent unfair identification of authors and admit of them. Research design, data and methodology: The study described literary research, standard research, phenomenon research, and empirical result without methodologies, statistical analysis and scientific test and investigated operation system of KODISA cases. Results: At publication of findings of the research, researchers shall identify the ones of production of the finding to allocate help of the research. Conclusions: Scientific journals shall be controlled to develop ability and to grow up and have a system. Researchers shall give direction of other scientific journals. The study made efforts to be a model. KODISA Edition Team shall make an effort to keep and develop. So far, no regulation of identification of authors has produced disturbance so terminologies should be uniformed. Researchers shall keep rules of identification of authors to uniform and regulate identification of authors, conditions of authors, and order and correspondent authors. KODISA enacted rules of identification of authors for the first time in Korea to develop science.

A Study on the Business Investment and Operation of O2O (Online-To-Offline) Combined Services by Industry (산업별 O2O 결합 서비스의 비즈니스 투자 및 운영에 관한 연구)

  • Jung, Byoungho;Joo, Hyungkun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.2
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    • pp.93-110
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    • 2022
  • The purpose of this study is to explore business investment and operation of O2O (Online-To-Offline) combined service. The study will analyze the necessary factors for growing the business by dividing the O2O service by industry. The Online-to-Offline is a method of inducing purchases of products and services by connecting between online and offline This research methodology organized the four stages of the analysis process. The analysis of all stages was performed with association rules in big data techniques. It is divided into the start-up period, growth period, maturity period, and decline period, and analysis is conducted on the business investment, expenditure cost, business operation, and conflict factors. As the research result, the first analysis has shown commonality with government subsidies, bank loans, and personal funds in all industries. The second analysis showed a lot of expenditure on labor costs of internal employees, marketing/sales, facility facilities, equipment, and equipment purchase costs. The third analysis showed difficulty in raising the investment resources necessary for business operations in all industries. The last analysis showed conflicts in the industry, businesses license, legal systems, and small business owners in all industries. This study contributed to the abundance and diversity of research methodologies in management information systems using association rules. In addition, the description of organizational development theory was updated while explaining the business investment and operation of O2O combined services. In practical implication, the O2O services include environmental factors that cause convergence between industries. Accordingly, this is required for new O2O services through new laws and systems and reorganization of existing laws and regulations.

Analysis of Electric Power System Using Data Mining Association Rule (데이터마이닝 연관 기법을 이용한 전력계통 고장 해석)

  • Lee, Joon-Sub;Kim, Min-Soo;Choi, Sang-Yule;Kim, Chul-Hwan;Kim, Ung-Mo
    • Proceedings of the KIEE Conference
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    • 2001.07a
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    • pp.214-216
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    • 2001
  • Data Mining is a issue of Database fields. Data mining is discovered optimally interesting rules for user, which are results of specific requirements of user. through past data. Through to analyze and to statical suppose interesting rules. we can prepare future faults of system. In this paper, we present a new way which is discovered and repaired faults of Electric Power system using Data Mining techniques.

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Structural Strength Assessment of Forward Cargo Hold for Kamsarmax CSR Bulk Carrier (Kamsarmax급 CSR Bulk Carrier의 Forward Cargo Hold 구조적 특성 및 안정성 검증)

  • Hwang, Sang-Wook;Park, Jeong-Jun
    • Special Issue of the Society of Naval Architects of Korea
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    • 2011.09a
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    • pp.17-20
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    • 2011
  • The International Association of Classification Societies (IACS) had developed the Common Structural Rules (CSR) for bulk carriers as per the needs noted above. ISO and IMO GBS (Goal-Based Standards) are now being developed in this regard. This study has been prepared to verity the strength of forward cargo hold of 82,000 DWT class bulk carriers. A cargo hold/tank 3-D FE model was established to assess the structural adequacy of the primary structural members with the loading conditions. Full breadth model was established for the analysis considering asymmetric nature of structural layout and loading conditions. To summarize this result of structural assessment based on IACS CRS for bulk carrier, it is benefit to design this kind of bulk carriers and to study the strength assessment for the similar type of bulk carriers.

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Automatic Adverb Error Correction in Korean Learners' EFL Writing

  • Kim, Jee-Eun
    • International Journal of Contents
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    • v.5 no.3
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    • pp.65-70
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    • 2009
  • This paper describes ongoing work on the correction of adverb errors committed by Korean learners studying English as a foreign language (EFL), using an automated English writing assessment system. Adverb errors are commonly found in learners 'writings, but handling those errors rarely draws an attention in natural language processing due to complicated characteristics of adverb. To correctly detect the errors, adverbs are classified according to their grammatical functions, meanings and positions within a sentence. Adverb errors are collected from learners' sentences, and classified into five categories adopting a traditional error analysis. The error classification in conjunction with the adverb categorization is implemented into a set of mal-rules which automatically identifies the errors. When an error is detected, the system corrects the error and suggests error specific feedback. The feedback includes the types of errors, a corrected string of the error and a brief description of the error. This attempt suggests how to improve adverb error correction method as well as to provide richer diagnostic feedback to the learners.

Automatic Processing of Predicative Nouns for Korean Semantic Recognition. (한국어 의미역 인식을 위한 서술성 명사의 자동처리 연구)

  • Lee, Sukeui;Im, Su-Jong
    • Korean Linguistics
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    • v.80
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    • pp.151-175
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    • 2018
  • This paper proposed a method of semantic recognition to improve the extraction of correct answers of the Q&A system through machine learning. For this purpose, the semantic recognition method is described based on the distribution of predicative nouns. Predicative noun vocabularies and sentences were collected from Wikipedia documents. The predicative nouns are typed by analyzing the environment in which the predicative nouns appear in sentences. This paper proposes a semantic recognition method of predicative nouns to which rules can be applied. In Chapter 2, previous studies on predicative nouns were reviewed. Chapter 3 explains how predicative nouns are distributed. In this paper, every predicative nouns that can not be processed by rules are excluded, therefore, the predicative nouns noun forms combined with the case marker '의' were excluded. In Chapter 4, we extracted 728 sentences composed of 10,575 words from Wikipedia. A semantic analysis engine tool of ETRI was used and presented a predicative nouns noun that can be handled semantic recognition language.

A Study on the Direct Transport of Rules of Origin in Korean FTAs (FTA 원산지규정상의 직접운송원칙에 관한 연구)

  • Lee, Young-Soo;Kwon, Soon-Koog
    • International Commerce and Information Review
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    • v.14 no.4
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    • pp.387-408
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    • 2012
  • This paper have examined the descriptive and legal approaches to the comparison and analysis of major content of direct transport in FTA rules of origin and the primary judicial precedents that arose during the executing process of FTAs. Preferential tariff treatment shall be applied to a good satisfying the requirement of this agreement(annex, article etc.,) and which is transported directly between the territories of the exporting party and importing party. However, products may be transported through territories of non-parties, provided that they do not undergo operations other than unloading, reloading, splitting-up of consignments or any operation designed to preserve them in good condition. During this period the products shall remain under customs control in the country of transit. The low perception of firms on the rules of origin was found to lead to breaking the rule and thus taking up losses. The FTA major countries enacted penalty rules against the violation of the rules of origin and bring civil and criminal suits and administrative sanctions. The types and level of penalties are subject to their domestic laws of each of those nations. With better recognition of major content of direct transport in FTA rules of origin and well-prepared countermeasures, firms will be able to enhance competitive advantage while benefiting from preferential tariffs.

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Selection of Key Management Targets for Claim Causes through Relational Analysis on the Causes of Change Order Claims

  • Min, Kwang-Ho;Ko, Gun-Ho;Jin, Chengquan;Hyun, Chang-Taek;Han, Sang-Won
    • International conference on construction engineering and project management
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    • 2017.10a
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    • pp.281-290
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    • 2017
  • As various stakeholders are involved in construction projects, disputes between the parties are more likely to occur, which is a very important issue for the participants in the projects. Claims in construction projects, however, are very complex and thus difficult to manage. In particular, as the cause of a claim in the preceding stage that has not been resolved in a timely manner has an effect on the cause of a claim in the following stage, it is difficult to find a point of compromise regarding a claim caused by the relationship between the causes that occur in the preceding and following stages. In this regard, this study sought to examine the rules for the generation of change order claims, which occur most frequently among the construction claims, and thus to select the key management targets through the analysis of the relationship between the causes of claims arising in the preceding and following stages for the efficient management of claims. It is expected that the use of rules for the generation of change order claims as well as of representative and similar cases will help the construction practitioners in judging claims, considering the relationships among the causes of the claims. Meanwhile, in this study, association analysis was conducted regarding the causes of the occurrence of change order claims in a design-build delivery method, and therefore, it is necessary to verify the effectiveness of the method when applied to other delivery methods.

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연관분석을 이용한 데이터마이닝 기법에 관한 사례연구

  • Ryu, Gwi-Yeol;Mun, Yeong-Su;Choi, Seung-Du
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.109-120
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    • 2006
  • Huge information has been made due to the current computing environment and could not be acceptable. People want the information which they can understand and accept easily. They may want not only simple information but also knowledge. That is why data mining becomes a center of information. We use RFM analysis in order to create customer score. Customers are classified into five groups(most oxcellenrexcellenycommoflowerilowest) for a various marketing activities. We can found the significant patterns in each group, and classify customers from loyal customers to leaving customers in the near future by the indirect data mining(e.g. association analysis) and the direct data mining(e.g. decision tree, logistic regression analysis, etc.), which are named in this study. Our research focuses on the advanced models by applying the association rules in data mining. Our results indicate that the indirect data mining and the direct data mining seem to have same outputs, but the former shows more clear pattern then the latter one.

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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.