• Title, Summary, Keyword: Association rules

Search Result 1,166, Processing Time 0.035 seconds

Secondary School Science Teachers' Emotional Display Rules and Emotional Labor Types (중등 과학교사의 감정표현규칙과 감정노동 유형)

  • Kim, Heekyong
    • Journal of The Korean Association For Science Education
    • /
    • v.37 no.4
    • /
    • pp.705-717
    • /
    • 2017
  • The purpose of the study is to explore secondary science teachers' emotional display rules, types of emotional labor, science-specific emotional display rules and the episodes of emotional labor. For this purpose, the survey to measure emotional labor of science teachers (The Emotional Labor of Science Teaching Scale: TELSTS) was developed and the participants were 145 secondary science teachers in Korea. Results showed that first, secondary science teachers recognized the emotional display rules defined by their schools, especially, positive display rules. Second, secondary science teachers showed that they were carrying out emotional labor in order to keep their emotional display rules in check. The mean value of responses to deep acting was high. Also, there were statistically significant differences in emotional labor depending on whether they were full-time or part-time teachers and their teaching career. Third, as a result of analyzing the specificity of science teachers, it was mainly related to the objective and logical image of science, and experimental instruction. Seventy-four percent (74%) of responses were negative or neutral emotional display rules. Finally, implications for science education are discussed.

Adaptive Customer Relation Management Strategies using Association Rules (연관 규칙을 이용한 적응적 고객 관계 관리 전략)

  • Han, Ki-Tae;Chung, Kyung-Yong;Baek, Jun-Ho;Kim, Jong-Hun;Ryu, Joong-Kyung;Lee, Jung-Hyun
    • Proceedings of the Korea Contents Association Conference
    • /
    • /
    • pp.84-86
    • /
    • 2008
  • The customer relation marketing in which companies can utilize to control and to get the filtered information efficiently has appeared. It is applying data mining to build the management that can even predict and recommend products to customers. In this paper, we proposed the adaptive customer relation management strategies using the association rules of data mining. The proposed method uses the association rules composes frequent customers with occurrence of candidate customer set creates the rules of associative customers. We analyzed the efficient feature of purchase customers using the hyper graph partition according to the lift of creative association rules. Therefore, we discovered strategies of the cross-selling and the up-selling about customers.

  • PDF

Non-linear regression model considering all association thresholds for decision of association rule numbers (기본적인 연관평가기준 전부를 고려한 비선형 회귀모형에 의한 연관성 규칙 수의 결정)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.24 no.2
    • /
    • pp.267-275
    • /
    • 2013
  • Among data mining techniques, the association rule is the most recently developed technique, and it finds the relevance between two items in a large database. And it is directly applied in the field because it clearly quantifies the relationship between two or more items. When we determine whether an association rule is meaningful, we utilize interestingness measures such as support, confidence, and lift. Interestingness measures are meaningful in that it shows the causes for pruning uninteresting rules statistically or logically. But the criteria of these measures are chosen by experiences, and the number of useful rules is hard to estimate. If too many rules are generated, we cannot effectively extract the useful rules.In this paper, we designed a variety of non-linear regression equations considering all association thresholds between the number of rules and three interestingness measures. And then we diagnosed multi-collinearity and autocorrelation problems, and used analysis of variance results and adjusted coefficients of determination for the best model through numerical experiments.

An Association Discovery Algorithm Containing Quantitative Attributes with Item Constraints (수량적 속성을 포함하는 항목 제약을 고려한 연관규칙 마이닝 앨고리듬)

  • 한경록;김재련
    • Journal of the Society of Korea Industrial and Systems Engineering
    • /
    • v.22 no.50
    • /
    • pp.183-193
    • /
    • 1999
  • The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In this paper, we propose an efficient algorithm for mining quantitative association rules with item constraints. For categorical attributes, we map the values of the attribute to a set of consecutive integers. For quantitative attributes, we can partition the attribute into values or ranges. While such constraints can be applied as a post-processing step, integrating them into the mining algorithm can reduce the execution time. We consider the problem of integrating constraints that are boolean expressions over the presence or absence of items containing quantitative attributes into the association discovery algorithm using Apriori concept.

  • PDF

Preventing the Musculoskeletal Disorders using Association Rule - Based on Result of Multiple Logistic Regression - (연관규칙을 이용한 근골격계 질환 예방 - 다변량 로지스틱 회귀분석의 결과를 기반으로 -)

  • Park, Seung-Hun;Lee, Seog-Hwan
    • Journal of the Korea Safety Management & Science
    • /
    • v.9 no.4
    • /
    • pp.29-38
    • /
    • 2007
  • We adapted association rules of data mining in order to investigate the relation among the factors of musculoskeletal disorders and proposed the method of preventing the musculoskeletal disorders associated with multiple logistic regression in previous study. This multiple logistic regression was difficult to establish the method of preventing musculoskeletal disorders in case factors can't be managed by worker himself, i.e., age, gender, marital status. In order to solve this problem, we devised association rules of factors of musculoskeletal disorders and proposed the interactive method of preventing the musculoskeletal disorders, by applying association rules with the result of multiple logistic regression in previous study. The result of correlation analysis showed that prevention method of one part also prevents musculoskeletal disorders of other parts of body.

The Problems and Solutions in the Laws and Regulations regarding Anti-Dumping in China (중국 반덤핑법제상의 문제점과 해결방안)

  • Choi, Seok-Beom
    • International Commerce and Information Review
    • /
    • v.12 no.3
    • /
    • pp.361-387
    • /
    • 2010
  • China has been the number one target of anti-dumping cases. In the middle of 1990s, China began to make anti-dumping rules to protect its domestic markets. The first anti-dumping regulation was mentioned in 1994 and the anti-dumping and anti-subsidy regulation was published in 1997. In 2001, China entered into the WTO and as a member of WTO, China is obliged to revise its anti-dumping rules in accordance with WTO's requirements. After that China amended anti-dumping rules in 2004 and it is still valid. Even though China makes considerable efforts to make the rules to be consistent with WTO Rules, China is still facing various difficulties such as lack of transparency, absence of definite deadlines, mismatch between rules, lack of clear interest criteria, overly hard questionnaires and inadequacy of judicial review and non-market economy. This paper deals with the current situation of anti-dumping system in China and the scheme of antidumping law and regulations and the main contents of that law and regulations. The purpose of this paper is to contribute to the enhancement of China's anti-dumping rules by studying the problems and solutions of the anti-dumping rules in China.

  • PDF

Answer Extraction of Concept based Question-Answering System (개념 기반 질의-응답 시스템에서의 정답 추출)

  • Ahn Young-Min;Oh Su-Hyun;Kang Yu-Hwan;Seo Young-Hoon
    • Proceedings of the Korea Contents Association Conference
    • /
    • /
    • pp.448-451
    • /
    • 2005
  • In this paper, we describe a method of answer extraction on a concept-based question-answering system. The concept-based question answering system is a system which extract answer using concept information. we have researched the method of answer extraction using concepts which analyzed and extracted through question analysing with answer extracting rules. We analyzed documents including answers and then composed answer extracting rules. Rules consist of concept and syntactic information, we generated candidates of answer through the rules and then chose answer.

  • PDF

An Efficient Tree Structure Method for Mining Association Rules (트리 구조를 이용한 연관규칙의 효율적 탐색)

  • Kim, Chang-Oh;Ahn, Kwang-Il;Kim, Seong-Jip;Kim, Jae-Yearn
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.27 no.1
    • /
    • pp.30-36
    • /
    • 2001
  • We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.

  • PDF

Personalized e-Commerce Recommendation System using RFM method and Association Rules (RFM 기법과 연관성 규칙을 이용한 개인화된 전자상거래 추천시스템)

  • Jin, Byeong-Woon;Cho, Young-Sung;Ryu, Keun-Ho
    • Journal of the Korea Society of Computer and Information
    • /
    • v.15 no.12
    • /
    • pp.227-235
    • /
    • 2010
  • This paper proposes the recommendation system which is advanced using RFM method and Association Rules in e-Commerce. Using a implicit method which is not used user's profile for rating, it is necessary for user to keep the RFM score and Association Rules about users and items based on the whole purchased data in order to recommend the items. This proposing system is possible to advance recommendation system using RFM method and Association Rules for cross-selling, and also this system can avoid the duplicated recommendation by the cross comparison with having recommended items before. And also, it's efficient for them to build the strategy for marketing and crm(customer relationship management). It can be improved and evaluated according to the criteria of logicality through the experiment with dataset collected in a cosmetic cyber shopping mall. Finally, it is able to realize the personalized recommendation system for one to one web marketing in e-Commerce.

A Data Mining Technique for Customer Behavior Association Analysis in Cyber Shopping Malls (가상상점에서 고객 행위 연관성 분석을 위한 데이터 마이닝 기법)

  • 김종우;이병헌;이경미;한재룡;강태근;유관종
    • The Journal of Society for e-Business Studies
    • /
    • v.4 no.1
    • /
    • pp.21-36
    • /
    • 1999
  • Using user monitoring techniques on web, marketing decision makers in cyber shopping malls can gather customer behavior data as well as sales transaction data and customer profiles. In this paper, we present a marketing rule extraction technique for customer behavior analysis in cyber shopping malls, The technique is an application of market basket analysis which is a representative data mining technique for extracting association rules. The market basket analysis technique is applied on a customer behavior log table, which provide association rules about web pages in a cyber shopping mall. The extracted association rules can be used for mall layout design, product packaging, web page link design, and product recommendation. A prototype cyber shopping mall with customer monitoring features and a customer behavior analysis algorithm is implemented using Java Web Server, Servlet, JDBC(Java Database Connectivity), and relational database on windows NT.

  • PDF