• 한국정보처리학회논문지
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• 제6권11호
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• pp.2863-2874
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• 1999

Apartment auction is a system that is used for the citizens to get a house. This paper deals with the implementation of a web-based intelligent decision support system using OLAP technique and data mining technique for auction decision support. The implemented decision support system is working on a real auction database and is mainly composed of OLAP Knowledge Extractor based on data warehouse and Auction Data Miner based on data mining methodology. OLAP Knowledge Extractor extracts required knowledge and visualizes it from auction database. The OLAP technique uses fact, dimension, and hierarchies to provide the result of data analysis by menas of roll-up, drill-down, slicing, dicing, and pivoting. Auction Data Miner predicts a successful bid price by means of applying classification to auction database. The Miner is based on the lazy model-based classification algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm to reflect the characteristics of auction database.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.57.5-57
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• 2001

This paper presents an enhanced web-based distributed system with Single Access Object Protocol(SOAP), which uses HTTP as a communication protocol and XML as a data presentation. The suggested system is applied into a Generic Equipment Model (GEM) for exchanging specified messages(SECS-II), which are encoded into XML presentation, between Equipment and Host via the web sorrel. In this paper, the designed system architecture and its soap components are presented.

• 대한산업공학회지
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• 제28권3호
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• pp.274-282
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• 2002

This paper discusses a multi-dimensional analysis for Customer Relationship Management (CRM). For this, We propose a decision-making methodology which employs three analysis models. The first model is a three-dimension positioning map to derive a strategy which achieves the Process Value Line (PVL). The second model is the web-shape analysis model to visibly understand the individual based on the customer CSI (Customer Satisfactory Index) data. The third model which supports the web-shape analysis model, is the relative satisfactory analysis model. It considers a satisfaction level after purchasing against before purchasing. Then we perform overall analysis based on the three analysis models to provide marketing strategies to decision makers.

• 한국농공학회논문집
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• 제56권6호
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• pp.93-102
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• 2014

Generally data loading is a laborous job to develop models. Meteorological data is basic input data for hydrological models, it is provided through websites of Korea Meteorological Administration (KMA). The website of KMA provides daily meteorological observation data with tabular format classified by years, items, stations. It is cumbersome to manipulate tabular format for model inputs such as time series and multi-item or multi-station data. The provider oriented services which broadcast restricted formed information have caused inconvenient processes. Tim O'Reilly introduces "Web 2.0" which focuses on providing a service based on data. The top ranked IT companies such as google, yahoo, daum, and naver provide customer oriented services with Open API (Application Programming Interface). A RESTful web service, typical implementation for Open API, consists URI request and HTTP response which are simple and light weight protocol than SOAP (Simple Object Access Protocol). The aim of this study is to develop a web-based service that helps loading data for human use instead of machine use. In this study, the developed RESTful web service provides Open API for manipulating meteorological data. The proposed Open API can easily access from spreadsheet programs, web browsers, and various programming environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1963-1978
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• 2015

With the advancement of mobile web environments, identification and analysis of the user behavior play a significant role and remains a challenging task to implement with variations observed in the model. This paper presents an efficient method for mining optimized user behavior prediction model using genetic algorithm on mobile web structure. The framework of optimized user behavior prediction model integrates the temporary and permanent register information and is stored immediately in the form of integrated logs which have higher precision and minimize the time for determining user behavior. Then by applying the temporal characteristics, suitable time interval table is obtained by segmenting the logs. The suitable time interval table that split the huge data logs is obtained using genetic algorithm. Existing cluster based temporal mobile sequential arrangement provide efficiency without bringing down the accuracy but compromise precision during the prediction of user behavior. To efficiently discover the mobile users' behavior, prediction model is associated with region and requested services, a method called optimized user behavior Prediction Model using Genetic Algorithm (PM-GA) on mobile web structure is introduced. This paper also provides a technique called MAA during the increase in the number of models related to the region and requested services are observed. Based on our analysis, we content that PM-GA provides improved performance in terms of precision, number of mobile models generated, execution time and increasing the prediction accuracy. Experiments are conducted with different parameter on real dataset in mobile web environment. Analytical and empirical result offers an efficient and effective mining and prediction of user behavior prediction model on mobile web structure.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.75-79
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• 1999

Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3B GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a file format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(eXtensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for. users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.11-19
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• 2018

최근 GIS(Geographic Information System)을 중심으로 다양한 정보를 지도위에 제공하고 있으며, 대표적으로 국외의 경우 구글맵, 오픈스트리트맵, 빙맵 등이 있고, 국내의 경우 네이버지도, 다음지도, 브이월드맵 등이 GIS 기술의 한 부분인 WMS(Web Map Service)를 이용하여 서비스를 제공하고 있다. 본 논문에서는 현재 서비스되고 있는 벡터장 데이터 정보를 이용하여, 조류의 흐름도 와 스트림라인의 표출 방안 알고리즘 연구 및 사용자 편의성을 고려한 해양예측모델 데이터의 가시화 방안에 대해 연구를 수행하였다. 기존의 조류 흐름도 표출 및 스트림라인 표출 알고리즘과 제안하는 방식의 성능을 비교를 하여, 기존의 기술 보다 2배 이상 빠른 표출이 되는 것을 확인하였다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.307-310
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• 2018

우리 사회는 데이터를 기반으로 진화 하고 있어 데이터분석을 할 수 있는 통계패키지가 오늘날 상용화 되고 있다. 상용화되고 있는 통계패키지를 이용해 본 논문에서는 통계패키지 R을 Model1구조가 아닌 Model2 MVC구조로 적용하여, 웹사이트의 유지보수와 코드 효율성을 증진시키고자 한다. 이를 이용하여 웹 스크래핑을 통한 데이터를 수집 후 데이터 분석을 토대로 사용자가 분석내용을 쉽게 이해할 수 있도록, 편의성을 증진시키고 검색 할 수 있는 웹사이트를 설계 및 구현 하고자 한다.

• 대한산업공학회지
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• 제32권1호
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• pp.18-28
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• 2006

Some issues which should be considered in an R&D project selection problem are as follows: First, quantitative analysis on the efficiencies of R&D projects is required to guarantee objective validity in the evaluation of the projects. For this reason, the methodology for selecting R&D projects should be based on mathematical models that perform quantitative analysis. Second, in general there are ordinal factors like Likert-scale in the data for evaluating R&D projects. Previous researches, however, couldn't suggest explicit methods incorporating these ordinal factors into models. Third, for the R&D project selection problems with limited resources like budget, it is necessary to decide the perfect ranking of the all projects. This paper develops a mathematical model that can be applicable to the problems of selecting R&D projects with the previous features. In this paper, we improve the original DEA model for evaluating efficiency to incorporate ordinal factors and suggest a new model which can decide the perfect ranking of all projects by merging the improved DEA model and AHP method. Furthermore a web-based R&D project selection system using the DEA/AHP model suggested in this paper is developed and illustrated.