• Title/Summary/Keyword: 아이디어 마이닝

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A Study on Extracting Ideas from Documents and Webpages in the Field of Idea Mining (아이디어 마이닝 분야에서 문헌과 웹페이지의 아이디어 발췌에 대한 연구)

  • Lee, Tae-Young
    • Journal of the Korean Society for information Management
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    • v.29 no.1
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    • pp.25-43
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    • 2012
  • The ideas and quasi-ideas useful for human's creation were drawn out from documents and webpages with extraction methods used in idea mining, opinion mining, and topic signal mining. The extraction methods comprised (1) decisive cue phrases, (2) cue figures and sounds, (3) contextual signals, and (4) discourse segmentations, They tested on the idea samples, such as thoughts, plans, opinions, writings, figures, sounds, and formulas. Methods (1), (3), and (4) received largely positive evaluation, judging the efficiency of 4 methods by F measure, a mixture of recall and precision ratio. In particular, decisive cue phrase method was effective to search idea and contextual signal method was effective to detect quasi-idea.

Grid Cell Based Spatial Clustering Method (그리드 셀 기반 공간 클러스터링 방법)

  • 이동규;정정수;문상호
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.10-12
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    • 2001
  • 대용량의 공간 데이터베이스로부터 임시적이고 유용한 지식을 자동적으로 추출하는 공간데이터 마이닝은 데이터양의 급격히 증가하면서 필요성이 더욱 증대되고 있다. 공간데이타 마이닝에서 데이터를 분석하여 유사한 그룹으로 분류하는 것은 중요한 분야이며, 이를 위해서는 공간 클러스터링 과정이 먼저 수행되어야 한다. 이러한 공간 클러스터링에서 가장 중요한 점은 클러스터링에 드는 비용의 감소와 점 공간객체에 한정된 클러스터링이 아닌 선 및 다각형 객체들의 클러스터링도 가능해야 한다. 본 본문은 이를 위하여 공간지역성을 보장하는 대표적인 공간분할 방법인 그리드 셀을 이용한다. 기존의 클러스터링에서 사용되는 객체들 간의 거리 계산을 인접한 그리드 셀들 간의 관계 연산으로 대체시키는 것이 핵심아이디어이다. 이 방법은 기존 클러스터링에서 객체들 간의 거리 계산으로 인한 비용을 현저하게 줄일 수 있고, 선 및 다각형 객체들의 클러스터링도 가능하게 하는 장점이 있다.

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A method of web Document Encoding Automatic Recognition for SNS Text Mining (SNS 텍스트 마이닝을 위한 웹문서 인코딩 자동 인식 기술 방안)

  • Mo, Eun-Su;Lee, Jae-Pil;Lee, Jae-Gwang;Lee, Jun-hyeon;Lee, Jae-Kwang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.415-417
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    • 2015
  • 사용자는 자신의 주변상황에 대한 정보를 수집 및 공유하기 위하여 SNS, 포탈사이트 및 커뮤니티를 사용한다. 본 논문에서는 사용자의 특성을 고려한 지역정보 수집 아이디어와 방법론을 제시한다. 또한 각각의 웹 시스템의 데이터를 수집하여, 광범위한 지역정보를 마이닝을 수행하고 가공해내는 시스템을 제안한다. 이를 위해 해결해야하는 이슈는 다음과 같다. 각 웹시스템의 문서들은 운영 체제에 따라 인코딩이 달리 사용되는데, 흔히 발생되는 오류 중 하나인 문자깨짐 현상이 그 예이다. 해결방법으로써 문서가 작성된 운영체제의 인코딩정보를 획득해야하며, 이 정보는 서버에서 제공하는 헤더정보에 명시되었거나 문서내에 내장되어 있다. 하지만 일부 웹사이트는 인코딩 정보를 제공하지 않으며, 국가별 인코딩이 다르기 때문에 이를 알기 쉽지않다. 그리하여 본 논문에서 제안하는 방법론은 텍스트 마이닝에 앞서 웹서버에서 제공하는 웹페이지를 읽어들여 인코딩정보를 획득하고, 문자의 깨짐없이 표시할 수 있도록 시스템을 구축하기 위해 Response Header, HTML의 meta tag 및 읽어드린 문서의 BOM(Byte Order Mark) 정보 및 인코딩 패턴을 통해 인식하도록 하여 글자 깨짐을 완하하도록 시스템을 설계하였다.

Analysis of Startup Process based on Process Mining Techniques: ICT Service Cases (프로세스 마이닝 기반 창업 프로세스 분석: ICT 서비스 창업 사례를 중심으로)

  • Min Woo Park;Hyun Sil Moon;Jae Kyeong Kim
    • Information Systems Review
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    • v.21 no.1
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    • pp.135-152
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    • 2019
  • Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.

Quick Decision Making Using Visual Dynamic Mining Tool;Spotfire (비쥬얼 다이나믹 마이닝 툴을 이용한 신속한 의사결정;Spotfire)

  • Kim, Seong-Ki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.89-91
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    • 2008
  • 엄청나게 쏟아져 나오는 데이터 홍수 속에서 오늘날의 업체와 연구기관에서는 신속하게 의사 결정을 해야 한다. 당면한 문제점들을 해결하기 위하여 접근할 수 있는 수많은 다양한 데이터 속에서 정확하게 경향을 파악하고 그 근본 원인을 찾아내어 신속하고 action을 행하는 것은 어떠한 회사에서도 성공에 있어서 가장 중요한 인자들 중의 하나이다. 초기 아이디어 도출, 연구 개발에서부터 제품의 생산, 판매 및 서비스에 이르기까지 모든 팀원들은 아주 빠르게 고도의 정확성으로 중요한 결정을 할 필요가 있다. 오늘날의 경쟁 시장에서 기업의 성공은 다른 경쟁자들보다 더 빠르게 결정을 할 수 있는 능력에 달려 있다. 이에 Sporfire에서는 사용자가 쉽고 빠르게 데이터를 분석하여 의사 결정을 할 수 있도록 다양한 기능을 제공하고 있다. 사용자가 SQL같은 전문 언어를 사용하지 않고도 다양한 데이터 source에서 쉽게 데이터를 가져오도록 Information Library를 이용할 수 있으며, 데이터베이스에 들어 있는 숫자들의 집합체를 다양한 차트와 도표들을 이용, 그래픽 적으로 제공해 줌으로써 데이터에 대하여 직관적으로 파악하여 신속하게 대응할 수 있도록 도와준다. 또한 그 결과물들을 MS 파워포인트, 엑셀시트, xml 등으로 저장하여 다른 용도로 사용할 수 있도록 하고 있다.

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Searching Sequential Patterns by Approximation Algorithm (근사 알고리즘을 이용한 순차패턴 탐색)

  • Sarlsarbold, Garawagchaa;Hwang, Young-Sup
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.5
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    • pp.29-36
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    • 2009
  • Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, is an important data mining problem with broad applications. Since a sequential pattern in DNA sequences can be a motif, we studied to find sequential patterns in DNA sequences. Most previously proposed mining algorithms follow the exact matching with a sequential pattern definition. They are not able to work in noisy environments and inaccurate data in practice. Theses problems occurs frequently in DNA sequences which is a biological data. We investigated approximate matching method to deal with those cases. Our idea is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call approximated pattern. The existing PrefixSpan algorithm can successfully find sequential patterns in a long sequence. We improved the PrefixSpan algorithm to find approximate sequential patterns. The experimental results showed that the number of repeats from the proposed method was 5 times more than that of PrefixSpan when the pattern length is 4.

Data-driven Co-Design Process for New Product Development: A Case Study on Smart Heating Jacket (신제품 개발을 위한 데이터 기반 공동 디자인 프로세스: 스마트 난방복 사례 연구)

  • Leem, Sooyeon;Lee, Sang Won
    • Journal of the Korea Convergence Society
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    • v.12 no.1
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    • pp.133-141
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    • 2021
  • This research suggests a design process that effectively complements the human-centered design through an objective data-driven approach. The subjective human-centered design process can often lack objectivity and can be supplemented by the data-driven approaches to effectively discover hidden user needs. This research combines the data mining analysis with co-design process and verifies its applicability through the case study on the smart heating jacket. In the data mining process, the clustering can group the users which is the basis for selecting the target groups and the decision tree analysis primarily identifies the important user perception attributes and values. The broad point of view based on the data analysis is modified through the co-design process which is the deeper human-centered design process by using the developed workbook. In the co-design process, the journey maps, needs and pain points, ideas, values for the target user groups are identified and finalized. They can become the basis for starting new product development.

Idea proposal of InfograaS for Visualization of Public Big-data (공공 빅데이터의 시각화를 위한 InfograaS의 아이디어 제안)

  • Cha, Byung-Rae;Lee, Hyung-Ho;Sim, Su-Jeong;Kim, Jong-Won
    • Journal of Advanced Navigation Technology
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    • v.18 no.5
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    • pp.524-531
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    • 2014
  • In this paper, we have proposed the processing and analyzing the linked open data (LOD), a kind of big-data, using resources of cloud computing. The LOD is web-based open data in order to share and recycle of public data. Specially, we defined the InfograaS (Info-graphic as a service), new business area of SaaS (software as a service), to support visualization technique for BA (business analytics) and Info-graphic. The goal of this study is easily to use it by the non-specialist and beginner without experts of visualization and business analysis. Data visualization is the process to represent visually and understand the data analysis easily. The purpose of data visualization is to deliver information clearly and effectively by chart and figure. The big data of public data are shared and presented in the charts and the graphics understood easily by various processing results using Hadoop, R, machine learning, and data mining of open source and resources of cloud computing.

A Study on the Research Trends on Open Innovation using Topic Modeling (토픽 모델링을 이용한 개방형 혁신 연구동향 분석 및 정책 방향 모색)

  • Cho, Sung-Bae;Shin, Shin-Ae;Kang, Dong-Seok
    • Informatization Policy
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    • v.25 no.3
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    • pp.52-74
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    • 2018
  • In February 2018, the Korean government established the "Comprehensive Plans for Government Innovation" in order to realize 'the people-centered government'. The core of the comprehensive plans is participation of the people, which is very similar to open innovation where social issues are solved by ideas and capabilities of the private sector rather than those of the government. Therefore, this study was conducted by extracting open innovation topics through topic modeling based on LDA(Latent Dirichlet Allocation) as English abstract-data from 2003, when the plans for open innovation was first announced, to April 2018. Based on the extracted results, it also conducted a comparative analysis with "Comprehensive Plans for Government Innovation." The study has significant implications in that it derives the relationship between the subjects, analyzes the present policies of Korea on open innovation and suggests directions for development.

A Study on Correlation Analysis of One-Person Housing Space Design Convergence Contents by Using Social Network Analysis (소셜 네트워크 분석 방법론을 활용한 1인 주거공간디자인 융합콘텐츠 상관관계 분석)

  • Park, Eun Soo;Kim, Ji Eun
    • Korea Science and Art Forum
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    • v.34
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    • pp.133-148
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    • 2018
  • Korea's housing structure is predicted that one-person housing will be the most common type of housing in Korea. Therefore, this study intends to derive contents for designing a one-person housing space considering the life of a rapidly increasing one-person householder. For this purpose, this study objectively derives the social, economic and cultural influencing factors of one-person households through big data analysis, and analyzed the correlation between contents using social network analysis methodology. In this paper, 60 core contents related to one person housing space were derived by applying big data analysis methodology. And through social network analysis, the most influential contents were derived from the space editing and space composition categories. This means that the residential space is an important part of the design idea that can flexibly respond to changes in the user's life. Based on this study, future research will focus on the concept and design methodology of one-person housing space.