• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.61-69
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• 2002

The aim of this study is the process of developing the information system of individual announced land price that can efficiently manage the land price work, improve public reliability in services and establish systematization of the national land information. The system is adapted to the test area, as a result, it is concluded that can improve the efficiency of management and the accuracy and objectivity of land price. Thus users can easily use it without professional knowledge since it offer convenient user' environment. Furthermore, it can rapidly search character and classification of land, use-zoning, the present condition of land price and so on. And it can find out change of land price and user according to search of history.

• Land and Housing Review
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• v.13 no.4
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• pp.45-53
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• 2022

This paper investigates empirically the lead-lag relation between the 'apartment price index' and 'Internet search volume'. This study uses Naver Trend Index as a proxy for Internet search volume. An increase in Internet search volume on the apartment price index indicates an increase in people's attention to an apartment. Different from previous studies exploring the relation between 'the released price index of the apartment' and 'Naver Trend Index', this study investigates the relation of the Naver Trend Index with 'the fundamental price component of an apartment' and 'the transitory price component of an apartment', respectively. The results of the Granger causality test reveal that there are bidirectional Granger causalities between the 'released price' and Naver Trend Index. In addition, the 'fundamental price component of an apartment' and Naver Trend Index have a feedback relation, while 'the transitory price component of an apartment' Granger causes the Naver Trend Index uni-directionally. The impulse response function analysis indicates that the shock of apartment prices increases Naver Trend Index in the first month. Overall, The close relationship between apartment prices and Naver Trend Index suggests that increases in the movement of apartment prices are positively associated with public attention on the apartment market.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1670-1678
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• 2004

Currently, Price comparison sites receive inputs of product information and price manually after being joined by releted shopping mall companies, and can't support automatically price fluctuation of products in real time. Therefore, this paper designs and implements web service system based on SOAP for interactive product order and price comparison dynamically using web service technologies in real time. This web service system composes web service client module including functions of product search, sort and order, and server module including functions of remote procedure call for product search and order. This web service system implements interchanging product information based on SOAP messages and can support independence of platform and flexible potability in environment conforming to SOAP, WSDL and UDDI standards.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.38-45
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• 2020

This study presents a systematic procedure for developing a short-term prediction deep learning model of rebar price using bidirectional LSTM, Random Search, data combination, Dropout. In general, users intuitively determine these values, making it time-consuming and repetitive attempts to explore results with good predictive performance, and the results found by these attempts cannot be guaranteed to be excellent. With the proposed approach presented in this study, the average accuracy of short-term price forecasts is approximately 98.32%. In addition, this approach could be used as basic data to produce good predictive results in a study that predicts prices with time series data based on statistics, including building materials other than rebars.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.129-141
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• 2015

Because land based aquaculture is restricted by high investment per rearing volume and control cost, good management planning is important in Land-based aquaculture system case. In this paper master production planning was made to decide the number of rearing, production schedule and efficient allocation of water resources considering biological and economic condition. The purpose of this article is to build the mathematical decision making model that finds the value of decision variable to maximize profit under the constraints. Stocking and harvesting decisions that are made by master production planning are affected by the price system, feed cost, labour cost, power cost and investment cost. To solve the proposed mathematical model, heuristic search algorithm is proposed. The model Input variables are (1) the fish price (2) the fish growth rate (3) critical standing corp (4) labour cost (5) power cost (6) feed coefficient (7) fixed cost. The model outputs are (1) number of rearing fish (2) sales price (3) efficient allocation of water pool.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.50-51
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• 2019

Globally, South Korea is a country that has a lot of $CO_2$ emissions and has steadily increased its total greenhouse gas emissions since the 1990s. With the recent implementation of the carbon emission trading system in Korea, the importance of calculating $CO_2$ emissions of construction equipment is increasing, hence the need for accurate calculation of environmental penalties through allocating carbon emission rights. This study presents a methodology to predict the price of carbon credits using big data analysis method. This methodology is based on correlating and regression analysis of trends in carbon emission prices and search volumes. This study aims to support faster and more accurate budget calculations in the planning of the construction process based on the predicted price of carbon emission rights.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.1-14
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• 2015

In this paper, we investigate the relationship between Internet search trends and stock market. Under the assumption that investors may use Internet search engine to obtain information for companies of their interests before taking actual investment actions, the relationship between the changes on Internet search volume and the fluctuation of trading volume as well as stock price of a company is analyzed with actual market data. A search trend investment strategy that reflects the changes on Internet search volume is applied to large enterprises' group and to small and medium enterprises' (SMEs) group, and the correlation between profit rate and trading volume is analyzed for each company group. Our search trend investment strategy has outperformed average stock market returns in both KOSPI and KOSDAQ markets during the seven-year study period (2007~2013). It is also shown that search trend investment strategy is more effective to SMEs than to large enterprises. The relationship between changes on Internet search volume and stock trading volume is stronger at SMEs than at large enterprises.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.27-51
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• 2007

We analyze the effects of the sellers' strateiges on the final bid prices in internet auctions. We focus on the following three strategies of the seller adoption of the buy-price, setting the starting bid price, and adoption of 'the effective fixed price' which means that the starting bid price is set near the buy-price. In addition, the number of units sold single-unit or multi-unit, and item characteristics, such as whether the food is a search product (functional product) or an experience product (non-functional product), are also considered. We use real data on bids for 4 items from an online auction site. We find that in an auction for experience products when sold as single units, adopting the buy-price strategy raises the final bid price. We also find that in multi-unit auctions, starting the auction at 'the effective fixed price' raises the final bid price.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.179-196
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• 1999

A cyber shopping mall is a place where consumers acquire the product information and make purchase decision in the cyber space. Even though there are many advantages over traditional malls, there are still several limitations to do shopping in an existing cyber mall. One of them is the absence of efficient search tool to handle various products specifications. Existing search systems usually support the "keyword search only" with limited product information. Consumers spend lots of their time and efforts in searching products and comparing them. Recently, some web sites provide the shopping mall comparison service that supports the additional search conditions such as price and maker. These services improve the situation but it is not still acceptable. In this paper, we propose an intelligent product search system based on a mediator which supports various conditional search for each product. Our system provides consumers with search results that satisfy purchase specifications. Our system is implemented in Visual basic and pert and experimental results show satisfactory performance.