• Title/Summary/Keyword: Structured data

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An Efficient Schema Extracting Technique Using DTD in XML Documents (DTD를 이용한 XML문서의 효율적인 스키마 추출 기법)

  • Ahn, Sung-Eun;Choi, Hwang-Kyu
    • Journal of Industrial Technology
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    • v.21 no.A
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    • pp.141-146
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    • 2001
  • XML is fast emerging as the dominant standard to represent and exchange data in the Web. As the amount of data available in the Web has increased dramatically in recent years, the data resides in different forms ranging from semi-structured data to highly structured data in relational database. As semi-structured data will be represented by XML, XML will increase the ability of semi-structured data. In this paper, we propose an idea for extracting schema in XML document using DTD.

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Tree-structured Clustering for Mixed Data (혼합형 데이터에 대한 나무형 군집화)

  • Yang Kyung-Sook;Huh Myung-Hoe
    • The Korean Journal of Applied Statistics
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    • v.19 no.2
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    • pp.271-282
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    • 2006
  • The aim of this study is to propose a tree-structured clustering for mixed data. We suggest a scaling method to reduce the variable selection bias among categorical variables. In numerical examples such as credit data, German credit data, we note several differences between tree-structured clustering and K-means clustering.

Measurement of the Internet Banking Customer Satisfaction using Structured Equation Model

  • Choi, Kyung-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.301-311
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    • 2005
  • This study has conducted to measure the internet banking customer satisfaction using structured equation model. Data was collected by e-mail system. Among survey panel who had experience of using Hanwha-Bank internet banking service, final samples were 2,848 respondents. The results showed that usage convenience and economy factor was most correlated with customer satisfaction. And we found that word-of-mouth behavior was affected customer satisfaction.

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A Tool for Transformation of Analysis to Design in Structured Software Development

  • Park, Sung-Joo;Lee, Yang-Kyu
    • Journal of Korean Institute of Industrial Engineers
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    • v.14 no.2
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    • pp.71-80
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    • 1988
  • The primary purpose of this study is to develop an automation tool capable of converting the specification of structured analysis into that of structured design. Structured Analysis and Structured Design Language (SASDL) is a computer-aided description language based on ERA model and particulariged by ISLDM/SEM. The automation tool utilizes the specifications of data flow diagram described in SASDL to produce their corresponding SASDL specification of structure chart. The main idea behind the automatic conversion process is to categorize the bubbles in data flow diagram and to determine the positions of the bubbles in structure chart according to their categories and the relative locations in data flow diagram. To make the problem into manageable size, the whole system is broken down into separate parts called activity units. A great deal of manual jobs, such as checking processes leveling, checking data derivation of processes, deriving structure chart from data flow diagram, checking any inconsistency between data flow diagram and structure chart and so forth, can be automated by using SASDL and conversion tool. The specification of structure chart derived by conversion tool may be used in an initial step of design to be refined by SASDL users.

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Korean TableQA: Structured data question answering based on span prediction style with S3-NET

  • Park, Cheoneum;Kim, Myungji;Park, Soyoon;Lim, Seungyoung;Lee, Jooyoul;Lee, Changki
    • ETRI Journal
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    • v.42 no.6
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    • pp.899-911
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    • 2020
  • The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

3D shape reconstruction using laser slit beam and image block (레이저슬릿광과 이미지블럭을 이용한 경면물체 형상측정알고리즘)

  • 곽동식;조형석;권동수
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.93-96
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    • 1996
  • Structured laser light is a widely used method for obtaining 3D range information in Machine Vision. However, The structured laser light method is based on assumption that the surface of objects is Lambertian. When the observed surfaces are highly specularly reflective, the laser light can be detected in various parts on the image due to a specular reflection and secondary reflection. This makes wrong range data and the image sensor unusable for the specular objects. To discriminate wrong range data from obtained image data, we have proposed a new algorithm by using the cross section of image block. To show the performance of the proposed method, a series of experiments was, carried out on: the simple geometric shaped objects. The proposed method shows a dramatic improvement of 3D range data better than the typical structured laser light method.

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The Preliminary Feasibility on Big Data Analytic Application in Construction

  • Ko, Yongho;Han, Seungwoo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.276-279
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    • 2015
  • Along with the increase of the quantity of data in various industries, the construction industry has also developed various systems focusing on collecting data related to the construction performance such as productivity and costs achieved in construction job sites. Numerous researchers worldwide have been focusing on developing efficient methodologies to analyze such data. However, applications of such methodologies have shown serious limitations on practical applications due to lack of data and difficulty in finding appropriate analytic methodologies which were capable of implementing significant insights. With development of information technology, the new trend in analytic methodologies has been introduced and steeply developed with the new name of "big data analysis" in various fields in academia and industry. The new concept of big data can be applied for significant analysis on various formats of construction data such as structured, semi-structured, or non-structured formats. This study investigates preliminary application methods based on data collected from actual construction site. This preliminary investigation in this study expects to assess fundamental feasibility of big data analytic applications in construction.

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Prediction of Agricultural Purchases Using Structured and Unstructured Data: Focusing on Paprika (정형 및 비정형 데이터를 이용한 농산물 구매량 예측: 파프리카를 중심으로)

  • Somakhamixay Oui;Kyung-Hee Lee;HyungChul Rah;Eun-Seon Choi;Wan-Sup Cho
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.169-179
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    • 2021
  • Consumers' food consumption behavior is likely to be affected not only by structured data such as consumer panel data but also by unstructured data such as mass media and social media. In this study, a deep learning-based consumption prediction model is generated and verified for the fusion data set linking structured data and unstructured data related to food consumption. The results of the study showed that model accuracy was improved when combining structured data and unstructured data. In addition, unstructured data were found to improve model predictability. As a result of using the SHAP technique to identify the importance of variables, it was found that variables related to blog and video data were on the top list and had a positive correlation with the amount of paprika purchased. In addition, according to the experimental results, it was confirmed that the machine learning model showed higher accuracy than the deep learning model and could be an efficient alternative to the existing time series analysis modeling.

Development of Color 3D Scanner Using Laser Structured-light Imaging Method

  • Ko, Youngjun;Yi, Sooyeong
    • Current Optics and Photonics
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    • v.2 no.6
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    • pp.554-562
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    • 2018
  • This study presents a color 3D scanner based on the laser structured-light imaging method that can simultaneously acquire 3D shape data and color of a target object using a single camera. The 3D data acquisition of the scanner is based on the structured-light imaging method, and the color data is obtained from a natural color image. Because both the laser image and the color image are acquired by the same camera, it is efficient to obtain the 3D data and the color data of a pixel by avoiding the complicated correspondence algorithm. In addition to the 3D data, the color data is helpful for enhancing the realism of an object model. The proposed scanner consists of two line lasers, a color camera, and a rotation table. The line lasers are deployed at either side of the camera to eliminate shadow areas of a target object. This study addresses the calibration methods for the parameters of the camera, the plane equations covered by the line lasers, and the center of the rotation table. Experimental results demonstrate the performance in terms of accurate color and 3D data acquisition in this study.