• Title/Summary/Keyword: 공간데이터 마이닝

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Location Generalization of Moving Objects for the Extraction of Significant Patterns (의미 패턴 추출을 위한 이동 객체의 위치 일반화)

  • Lee, Yon-Sik;Ko, Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.1
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    • pp.451-458
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    • 2011
  • In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.

Pattern Analysis for Civil Complaints of Local Governments Using a Text Mining (텍스트마이닝에 의한 지자체 민원청구 패턴 분석)

  • Won, Tae Hong;Yoo, Hwan Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.3
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    • pp.319-327
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    • 2016
  • Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

A Study on the Online Perception of Chabak Using Big Data Analysis (빅데이터 분석을 통한 차박의 온라인 인식에 대한 연구)

  • Kim, Sae-Hoon;Lee, Hwan-Soo
    • The Journal of Society for e-Business Studies
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    • v.26 no.2
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    • pp.61-81
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    • 2021
  • In the era of untact, the "Chabak" using cars as accommodation spaces is attracting attention as a new form of travel. Due to the advantages, including low costs, convenience, and safety, as well as the characteristics of the vehicle enabling independent travel, the demand for Chabak is continuously increasing. Despite the rapid growth of the market and related industries, little academic has investigated this trend. To establish itself as a new type of travel culture and to sustain the growth of related industries, it is essential to understand the public perception of Chabak. Therefore, based on the marketing mix theory and big data analysis, this study analyzes the public perception of Chabak. The results showed that Chabak has established itself as a consumer-led travel culture, contributing to the aftermarket growth of the automobile industry. Additionally, consumers were found to be increasingly inclined to enjoy travel economically and wisely, and actively share information through social media. This initial study on the new travel trend of Chabak is significant in that it employs big data analysis on a theoretical basis.

A Method for Optimal Moving Pattern Mining using Frequency of Moving Sequence (이동 시퀀스의 빈발도를 이용한 최적 이동 패턴 탐사 기법)

  • Lee, Yon-Sik;Ko, Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.1
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    • pp.113-122
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    • 2009
  • Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

Outdoor Healing Places Perception Analysis Using Named Entity Recognition of Social Media Big Data (소셜미디어 빅데이터의 개체명 인식을 활용한 옥외 힐링 장소 인식 분석)

  • Sung, Junghan;Lee, Kyungjin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.50 no.5
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    • pp.90-102
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    • 2022
  • In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.

Trend Analysis of Barrier-free Academic Research using Text Mining and CONCOR (텍스트 마이닝과 CONCOR을 활용한 배리어 프리 학술연구 동향 분석)

  • Jeong-Ki Lee;Ki-Hyok Youn
    • Journal of Internet of Things and Convergence
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    • v.9 no.2
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    • pp.19-31
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    • 2023
  • The importance of barrier free is being highlighted worldwide. This study attempted to identify barrier-free research trends using text mining. Through this, it was intended to help with research and policies to create a barrier free environment. The analysis data is 227 papers published in domestic academic journals from 1996 when barrier free research began to 2022. The researcher converted the title, keywords, and abstract of an academic thesis into text, and then analyzed the pattern of the thesis and the meaning of the data. The summary of the research results is as follows. First, barrier-free research began to increase after 2009, with an annual average of 17.1 papers being published. This is related to the implementation guidelines for the barrier-free certification system that took effect on July 15, 2008. Second, results of barrier-free text mining i) As a result of word frequency analysis of top keywords, important keywords such as barrier free, disabled, design, universal design, access, elderly, certification, improvement, evaluation, and space, facility, and environment were searched. ii) As a result of TD-IDF analysis, the main keywords were universal design, design, certification, house, access, elderly, installation, disabled, park, evaluation, architecture, and space. iii) As a result of N-Ggam analysis, barrier free+certification, barrier free+design, barrier free+barrier free, elderly+disabled, disabled+elderly, disabled+convenience facilities, the disabled+the elderly, society+the elderly, convenience facilities+installation, certification+evaluation index, physical+environment, life+quality, etc. appeared in a related language. Third, as a result of the CONCOR analysis, cluster 1 was barrier-free issues and challenges, cluster 2 was universal design and space utilization, cluster 3 was Improving Accessibility for the Disabled, and cluster 4 was barrier free certification and evaluation. Based on the analysis results, this study presented policy implications for vitalizing barrier-free research and establishing a desirable barrier free environment.

A Study of SBC Clustering Technology for 3D Environmental Modeling (3차원 환경 모델링을 위한 SBC 클러스터링 기술 연구)

  • Lee, Jun-Yeob;Oh, Jong-woo;Lee, DongHoon
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.167-167
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    • 2017
  • 스마트팜 내부의 3차원 공간의 온도, 습도, 기압, 공기질 분석을 통한 돈사 미세 조절 기술에 대한 연구가 진행 중이다. 해당 특성 중에서 기압을 제외한 환경인자들은 돈사 내의 구조 특성상 위치별로, 시간별로 매우 상이한 변이의 형태를 보인다. 일정 시점을 기준으로 계측 지점 이외의 지점에 대한 환경인자들을 공간적으로 추정하는 기술은 대표적으로 컴퓨터 분석 기술에 의존하고 있다. 시간 복잡도가 매우 높은 CFD(Computer Fluid Dynamics) 방식은 정밀도 측면에서 유리하나, 상응하는 제어 기술/하드웨어 등의 부재로 모델링 결과의 활용도가 낮다고 볼 수 있다. 본 연구에서는 CFD를 수행하는 과정에 있어 실질적으로 유효한 단위로 공간 분해능을 낮추고, 동등한 크기의 세부 공간에 대한 모델링을 병렬적으로 수행하기 위한 방안을 연구하였다. 실험적으로 돈사 환경을 3차원으로 구성하기 위하여, 공기 흡입구, 배출구, 기둥, 덕트 요소를 포함시켰다. 실내 공간을 1차적으로 가로, 세로, 높이방향으로 $3{\times}3{\times}3$ 균등 분배한 후 3차원 행렬로 분할하였다. 각 분할된 행렬에 대한 연산 수행을 위하여 현재까지 대중에 공개된 SBC(Single Board Computer) 중 가장 높은 연산 수행 능력이 있는 Odroid-XU4(Hardkernel, AnYang, Korea) 16식을 병렬 클러스터링 기술로 연동하였다. 하나의 AP당 8개의 코어가 내장되어 있으므로, 총 128개의 코어를 이용하여 동시에 128개의 3D 정방행렬 연산이 가능하도록 구성하였다. 모델링을 위한 수학적 모델로는 실험적으로 Steady turbulent model (Newtonian coefficient)을 이용하였다. 클러스터링을 이용한 병렬 처리의 특성상 균등한 정보량을 동시에 배분해야 하므로 108 ($27{\times}4$)개의 코어를 이용하여 1차적으로 나뉜 공간을 다시 4등분하여 동시에 $12{\times}12{\times}12$에 해당하는 공간 분해능에 대한 처리를 동시에 수행할 수 있도록 하였다. 2단계에 걸쳐 분할한 공간 세그먼트에 대한 클러스터링 연산 수행 결과 초당 15회 정도의 연산을 수행할 수 있었으며, 시간 분해능을 100으로 설정한 경우 약 5초가 수행되었다. 선행적으로 수행하였던 CFD 모델링 (OpenFOAM)과 비교하였을 때 상대적으로 정밀도가 낮은 3차원 모델링 결과를 얻을 수 있었다. 모델링에 소요되는 시간을 비약적으로 경감 시킨 장점을 살려 적정한 공간 분할 기법과 추가로 발생하는 다수의 바운더리 조건을 근사적으로 추정할 수 있는 데이터 마이닝 기술이 보완되어야 할 것이다.

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Feature Subset Selection in the Induction Algorithm using Sensitivity Analysis of Neural Networks (신경망의 민감도 분석을 이용한 귀납적 학습기법의 변수 부분집합 선정)

  • 강부식;박상찬
    • Journal of Intelligence and Information Systems
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    • v.7 no.2
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    • pp.51-63
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    • 2001
  • In supervised machine learning, an induction algorithm, which is able to extract rules from data with learning capability, provides a useful tool for data mining. Practical induction algorithms are known to degrade in prediction accuracy and generate complex rules unnecessarily when trained on data containing superfluous features. Thus it needs feature subset selection for better performance of them. In feature subset selection on the induction algorithm, wrapper method is repeatedly run it on the dataset using various feature subsets. But it is impractical to search the whole space exhaustively unless the features are small. This study proposes a heuristic method that uses sensitivity analysis of neural networks to the wrapper method for generating rules with higher possible accuracy. First it gives priority to all features using sensitivity analysis of neural networks. And it uses the wrapper method that searches the ordered feature space. In experiments to three datasets, we show that the suggested method is capable of selecting a feature subset that improves the performance of the induction algorithm within certain iteration.

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A study of the vitalization strategy for public sports facility through big-data (빅데이터 분석을 활용한 기금지원 체육시설 활성화 방안)

  • Kim, Mi-ok;Ko, Jin-soo;Noh, Seung-Chul;Chung, Jae-Hoon
    • Journal of Digital Convergence
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    • v.15 no.2
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    • pp.527-535
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    • 2017
  • As interest increases in health promotion through sports, demand for public sports facilities is steadily growing. However, there is a lack of research on operation and management compared with the supply plan of public sports facility. In this context, the aim of this study is to address problems of management of public sports centers and suggest strategies for vitalizing the facilities through the big-data. The data are collected from web such as news, blog, and cafe for one year in 2015. From the big-data, We can find that the national sports centers and the open gyms showed similar users' behavior but showed different needs. Both facilities have been used as sports and leisure area and have a high percentage of visitors for other purposes such as walking, picnics, etc. However, while the national sports facilities which were used for more specialized programs, the open sports center were used as leisure space.

Analysis of Domestic Security Solution Market Trend using Big Data (빅데이터를 활용한 국내 보안솔루션 시장 동향 분석)

  • Park, Sangcheon;Park, Dongsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.5
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    • pp.492-501
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    • 2019
  • To use the system safely in cyberspace, you need to use a security solution that is appropriate for your situation. In order to strengthen cyber security, it is necessary to accurately understand the flow of security from past to present and to prepare for various future threats. In this study, information security words of security/hacking news of Naver News which is reliable by using text mining were collected and analyzed. First, we checked the number of security news articles for the past seven years and analyzed the trends. Second, after confirming the security/hacking word rankings, we identified major concerns each year. Third, we analyzed the word of each security solution to see which security group is interested. Fourth, after separating the title and the body of the security news, security related words were extracted and analyzed. The fifth confirms trends and trends by detailed security solutions. Lastly, annual revenue and security word frequencies were analyzed. Through this big data news analysis, we will conduct an overall awareness survey on security solutions and analyze many unstructured data to analyze current market trends and provide information that can predict the future.