• 한국정보과학회논문지:소프트웨어및응용
• /
• 제37권2호
• /
• pp.155-160
• /
• 2010

본 논문은 비교마이닝(comparison mining)의 일환인 비교 문장 유형 자동 분류에 관하여 연구한다. 비교마이닝은 텍스트 마이닝의 한 분야로서 대용량의 텍스트를 대상으로 비교 관계를 분석하며, 크게 세 단계의 과정을 거치게 되는데 첫 번째 단계는 대용량의 문서에서 비교 문장만을 식별 후 추출해 내는 과정이고, 두 번째 단계는 추출된 비교 문장들을 비교 유형별로 분류하는 과정이며, 앞의 두 선행 과정이 끝나면 유형별로 비교 속성을 추출 및 비교 관계를 분석하는 세 번째 단계를 수행하게 된다. 본 연구에서는 변환 기반 학습(transformation-based learning) 기법을 이용하여 비교 문장들을 일곱 가지의 유형으로 자동 분류하는 두 번째 과제를 수행한다. 자연어 처리 분야 여러 부문에서 사용되고 있는 변환기반 학습은 오류를 감소시키는 최적의 규칙을 자동으로 생성하여 정답을 찾아가는 규칙 기반 학습 방법이다. 웹상의 다양한 도메인에서 추출된 비교 문장들을 대상으로 유형 분류를 수행한 결과 정확도 80.01%의 성능으로 일곱 가지 유형을 분류할 수 있었다.

• 벤처창업연구
• /
• 제5권1호
• /
• pp.81-91
• /
• 2010

The article contains comparative analysis of global, regional, local mining review in comparison with the Republic of Kazakhstan. At the article is considered the condition, production and consumption raw materials in the world. For Kazakhstan this branch is one of the most important, which is defining not only the level of the economic development of the country, but also its economical safety, export potential, opportunities for further development. The article represents practical interest for students, masters, doctors, and experts of the branch.

• 한국자기학회:학술대회 개요집
• /
• 한국자기학회 1998년도 춘계연구발표회 논문개요집
• /
• pp.18-19
• /
• 1998

• Asian Journal of Innovation and Policy
• /
• 제12권3호
• /
• pp.304-322
• /
• 2023

Text data mining ('big data methods') is one of the most widely used approaches during the COVID-19 pandemic. In particular, text data mining on Scopus databases or Web of Science (WoS). Text data mining is widely used to collect literature for later bibliometric analysis, and in the end, it becomes a literature review article. Therefore, in this article, we reveal the trend of publication of literature reviews in Scopus journals from Indonesia, Japan, South Korea, Vietnam, Singapore, and Malaysia. This article describes two essential parts, namely 1) a comparison of international publication trends and subject area of literature review publications, and 2) a comparison of Top 5 for Authors, Affiliation, Source Title, and Collaboration Country.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제8권1호
• /
• pp.1-5
• /
• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• International journal of advanced smart convergence
• /
• 제5권1호
• /
• pp.30-33
• /
• 2016

With the advent of big data, data mining is more increasingly utilized in various decision-making fields by extracting hidden and meaningful information from large amounts of data. Even as exponential increase of the request of unrevealing the hidden meaning behind data, it becomes more and more important to decide to select which data mining algorithm and how to use it. There are several mainly used data mining algorithms in biology and clinics highlighted; Logistic regression, Neural networks, Supportvector machine, and variety of statistical techniques. In this paper it is attempted to compare the classification performance of an exemplary algorithm J48 and REPTree of ML algorithms. It is confirmed that more accurate classification algorithm is provided by the performance comparison results. More accurate prediction is possible with the algorithm for the goal of experiment. Based on this, it is expected to be relatively difficult visually detailed classification and distinction.

• Communications for Statistical Applications and Methods
• /
• 제8권2호
• /
• pp.531-541
• /
• 2001

In this study, we compare the capabilities of the data mining tools of the most updated version objectively and provide the useful information in which enterprises and universities chose them. In particular, we compare the SAS/Enterprise Miner 3.0, SPSS/Clementine 5.2 and IBM/Intelligent Miner 6.1 which are well known and easily gotten.

• 대한수학회논문집
• /
• 제33권3호
• /
• pp.985-999
• /
• 2018

This paper is devoted to the existence and uniqueness of $L^p$ (p > 1) solutions for general time interval multidimensional backward stochastic differential equations (BSDEs for short), where the generator g satisfies a ($p{\wedge}2$)-order weak monotonicity condition in y and a Lipschitz continuity condition in z, both non-uniformly in t. The corresponding stability theorem and comparison theorem are also proved.

• 산업경영시스템학회지
• /
• 제25권5호
• /
• pp.46-52
• /
• 2002

Today's database system needs to collect huge amount of questionnaire that results from development of the information technology by the internet, so it has to be administrable. However, there are many difficulties concerned with finding analytic data or useful information in the high capacity-database. Data mining can solve these problems and utilize the database. Questionnaire analysis that uses data mining has drawn relevant patterns that did not look or was tended to overlook before. These patterns can be applied by a new business rule. The purpose of this research is to analyze the questionnaire results and to present the result that can help to make decision easily with data mining. Recognition and analysis about these techniques of data mining show suitable type of questionnaire survey. This research focus on the form of present composition and the model of suitable questionnaire to analyze the type of it. Also, the comparison between the actual questionnaire result and the conventional statistical analysis is examined.

• 벤처창업연구
• /
• 제4권2호
• /
• pp.21-58
• /
• 2009

The Purpose of this study is working out of the scientific-theoretical and practical recommendations directed on perfection of strategic planning of development of the enterprises of mining and gold mining branch. The methodological basis of research is based on the economic theory developed by a domestic and foreign science. At processing, generalisation and a writing of materials of the master's thesis following methods were applied: - supervision, - comparison, - the analysis and synthesis, - methods of an induction and deduction, - statistical groupings, - average and relative sizes, - the system approach. Finally, the theoretical and practical importance of this research consists that results of research will allow generating a basis of statement of effective system of strategic planning of a long-term sustainable development of the gold mining enterprises reducing risk of acceptance of inefficient strategic decisions. I would like to express many thanks to the NGO "Semey- My Home" and "EastGeoResources" LLP for their help and support in providing the data collection and data analysis stages of my research from 2006.