• Title/Summary/Keyword: Association Rules Analysis

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Pattern Analysis of Comorbidity and Multimorbidity in Reference to the 7th KNHANES (국민건강영양조사를 이용한 동반질환 및 다중이환의 패턴분석)

  • Lee, Hyun-Ju;Myoung, Sungmin
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.699-700
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    • 2021
  • This study investigated patterns of co-occuring chronic diseases and disorders in old ages. For this purpose, we utilized data from the Korean National Health and Nutrition Examination Survey for 3,734 old adults aged over 65. Data on 18 conditions were obtained, and analyzed using network analysis, associated rule mining, cluster analysis. The majority of participants has multimorbidity. Association rules analysis reveals unexpected comorbidities with high lift and confidence. Also, some morbidity clusters were present. Diabetes and emotional disorder had the greatest comorbidity and represent complex comorbid conditions. Old age is characterized by a complex pattern of multimorbidity and comorbidity. In conclusion, particular combinations of morbidities were very prevalent and will be needed to policy of health care interventions for old ages.

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Association Rules Analysis Between the Types and Causes of Disputes in Construction Projects (연관규칙 분석을 통한 건설공사 분쟁유형과 분쟁원인의 연관성 분석에 관한 연구)

  • Jang, Se Rim;Kim, Han Soo
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.5
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    • pp.3-14
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    • 2022
  • Construction projects have high potentials of claims among a variety of stakeholders. Claims on their own are not disputes but they have high potentials leading to disputes if agreements are not made between parties due to conflicting opinions. In the event of the construction disputes between clients and contractors, it could give negative impacts to both parties and, to minimize or pro-actively manage construction disputes, the role of clients is more significant. The objective of the study is to analyze a level of associations between the types of disputes and causes of construction projects based on the association rule analysis, and to identify and discuss key characteristics and implications from client's perspectives. The study analyzes associations between the types of disputes and causes, and also identifies those with a high level of associations. It also presents the outcomes of more systematic analysis compared to descriptive statistics just based on frequencies. Through the analysis of the data cases, the study proposes the directions to resolve the causes of disputes from client's perspectives. It can assist to improve understandings of the relationships between the types of disputes and causes and to pro-actively manage the disputes of construction projects.

A Case Study on Characteristics of Gender and Major in Career Preparation of University Students from Low-income Families: Application of Text Frequency Analysis and Association Rules (저소득층 대학생들의 진로준비과정에서의 성별·전공별 특성에 대한 사례연구: 텍스트 빈도분석과 연관분석의 적용)

  • Lee, Jihye;Lee, Shinhye
    • Journal of Digital Convergence
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    • v.16 no.12
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    • pp.61-69
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    • 2018
  • This study aims to understand and to infer the implications from the career preparation experiences of low-income university students in the context of high youth unemployment rate and the polarization of the social classes. For this purpose, we selected 13 university students who received scholarship from the S scholarship foundation and conducted analysis using text mining techniques based on the six-time interviews. According to the results, university students seem to be influenced by home environment and income level when recalling previous academic experience or designing career during the interview process. Also, these differences were found to have different characteristics according to gender and major. This study is meaningful in that the qualitative research data is analyzed by applying the text mining technique in a convergent way. As a result, the college life and career preparation of low-income university students were explored through the frequency and relation of words.

An Analysis on the Predictor Keyword of Successful Aging: Focused on Data Mining (데이터마이닝을 활용한 성공적 노후 예측 키워드 분석)

  • Hong, Seo-Youn
    • The Journal of the Korea Contents Association
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    • v.20 no.3
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    • pp.223-234
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    • 2020
  • This research is the association rule analysis using Apriori algorithm of data mining focusing on 32 predictive key words extracted from Hong (2019) affecting successful aging in Korea. And, to examine rules and patterns of those key words or predictive variables, this research used support, confidence, and lift. The data was analyzed with the R version 3. 5. 1 program, and visualized using arulesViz package and visNetwork. It was found that the variables highly associated with successful aging in Korea were 'hobby', 'volunteer service', 'preparation', and 'exercise'. This research concludes that, the variable which needs to be considered first of all for successful aging in Korea is 'hobby', followed by 'volunteer service', 'preparation', and 'exercise'.

Voter Perceptions and Behavior in East Asian Mixed Systems

  • Rich, Timothy S.
    • Journal of Contemporary Eastern Asia
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    • v.12 no.1
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    • pp.21-34
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    • 2013
  • How do mixed legislative systems shape voter behavior and public perceptions? Through an analysis of the electoral systems in Japan, South Korea, and Taiwan, this paper evaluates the extent to which the public in these three countries understand their mixed systems and whether claims of voter ignorance translate into irrational voting behavior based on the institutional effects of mixed systems. Through a multi-method approach including data from outside of East Asia, this analysis seeks to determine whether these three cases exhibit patterns consistent with other mixed systems. Empirical analysis affirms levels of strategic voting consistent with comprehension of electoral rules. Furthermore, this analysis suggests a disconnect between practical knowledge and electoral expectations.

Linguistic Theory in India and Panini (인도의 언어이론과 파니니)

  • 김형엽
    • Lingua Humanitatis
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    • v.1 no.2
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    • pp.123-139
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    • 2001
  • In the history of linguistics in the world the scholars in India could be regarded as the representative linguists, who had provided the cornerstone of the academic development at linguistics. Without looking into the contents of Indian linguistic theories devised and developed in the past it would be almost impossible to account for the origin of descriptive linguistics and historical linguistics. These linguistics trends became full-fledged in 19 and 20 century and are still accepted by a lot of researchers in order to analyze newly revealed languages and train students only coming up the toddling level of linguistic studies. In this paper I will show how far the influence of Indian linguistics has colored the flow of linguistic growth historically. Especially through the analysis of Panini grammar I will prove the intimate relationship between the Indian linguistic theory and the generative grammar - it is the most active theory at present. The methods that Panini applied to constitute the rules like sutra include lots of information, that also could be discovered at the rules postulated in the generative grammar. One of the common features found at both linguistic theories is the simplicity of rule representation. At the generative grammar a rule has to be established without any redundancy. When certain number of sounds like p, b, m show the same phonological. change relevant to lips (labial in linguistic term) different rules need not to be given for each sound separately. It is better to find a way of putting the sounds together in a rule with grouping the 3 sounds with the shared phonetic feature 'labial'. In Panini grammar the form of a rule was decided based on the simplicity, too. For example, sutra 6.1.77 shows the phonological connection between the vowels i, u r 1 and the semi-vowels y, v, r, 1. However, it does not require to postulate 4 individual rules respectively. Instead a rule in which the vowels and the semi-vowels are involved is suggested, and linguistically the rule make it clear that the more simpler the rules will be the better they can reflect the efficiency of human language acquisition. Although the systems introduced at Panini grammar have some sense of distance from the language education itself we cannot deny the fact that the grammar formulates the a turning point of linguistic development. It is essential for us to think over the grammar from the view point of the modem linguistic theories to understand their root and trunk more thoroughly. It will also help us to predict in which way linguistic tendency will proceed to in future.

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Design and Implementation of a Korean Analysis System for Multi-lingual Query Answering (다국어 질의응답을 위한 한국어 해석 시스템 설계 및 구현)

  • Kang, Won-Seog;Hwang, Do-Sam
    • The Journal of Korean Association of Computer Education
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    • v.7 no.4
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    • pp.43-50
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    • 2004
  • Multi-lingual query answering system is the system which answers on the queries with several languages. LASSO[l] is the system that aims to answer the multi-lingual query. In this paper, we design and implement a Korean analysis system for LASSO. The Korean analysis system for query answering needs processing techniques of dialogue style. And the system must be practical and general so as to use on various domains. This system uses not dialogue processing techniques with high cost and low utility but heuristic rules with low cost and high utility. It is designed and implemented as a Korean interface of multi-lingual query answering system. The techniques of this system highly contribute to information retrieval and Korean analysis researches.

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Assoication Rule Analysis between lifestyle risk behaviors and multimorbidity: Findings from KHANES (국민건강영양조사 자료를 활용한 라이프스타일 위험요인과 다중이환간의 연관관계분석)

  • Hyun-Ju Lee;Sungmin Myoung
    • The Journal of Korean Society for School & Community Health Education
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    • v.25 no.1
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    • pp.29-41
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    • 2024
  • Objectives: This study used an efficient data mining algorithm to explore association rules between the lifestyle risk behaviors and multimorbidity (having more than one chronic disease) in Korean adults. Methods: We used data from the 8th Korean National Health and Nutrition Examination Survey(2019-2020) for 7,609 adults aged ≥19 years. This study was undertaken where 6 lifestyle risk behaviors and 11 morbidities were analyzed using R and Rstudio for the ARM. Results: Among 117 association rules, combinations of hypertension, dyslipidemia and diabetes, hypertension were important role in inadequate sleep, physical inactivity and inadequate weight. Conclusion: The findings of this study are significant because they demonstrate the importance of lifestyle risk factors and the role of multiple chronic diseases using big data analytics such as association rule mining. We recommend developing selective and focused health education programs, such as exercise programs to address physical inactivity, dietary interventions to address inadequate weight, and mental health education programs to address inadequate sleep.

An Investigation on Expanding Co-occurrence Criteria in Association Rule Mining (온라인 연관관계 분석의 장바구니 기준에 대한 연구)

  • Kim, Mi-Sung;Kim, Nam-Gyu
    • CRM연구
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    • v.4 no.2
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    • pp.19-29
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    • 2011
  • There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems.

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Development of Automatic Rule Extraction Method in Data Mining : An Approach based on Hierarchical Clustering Algorithm and Rough Set Theory (데이터마이닝의 자동 데이터 규칙 추출 방법론 개발 : 계층적 클러스터링 알고리듬과 러프 셋 이론을 중심으로)

  • Oh, Seung-Joon;Park, Chan-Woong
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.6
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    • pp.135-142
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    • 2009
  • Data mining is an emerging area of computational intelligence that offers new theories, techniques, and tools for analysis of large data sets. The major techniques used in data mining are mining association rules, classification and clustering. Since these techniques are used individually, it is necessary to develop the methodology for rule extraction using a process of integrating these techniques. Rule extraction techniques assist humans in analyzing of large data sets and to turn the meaningful information contained in the data sets into successful decision making. This paper proposes an autonomous method of rule extraction using clustering and rough set theory. The experiments are carried out on data sets of UCI KDD archive and present decision rules from the proposed method. These rules can be successfully used for making decisions.