• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.27-35
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• 2021

The study intends to identify the effects of infrastructure property on an apartment house by analyzing the price variation affected by factors constituting the quality of the transit services of each individual station in urban railway system based on hedonic price model. The research findings indicate that the prices depending on the transit users have increased from 7.8% to 12.2% in Seoul and decreased from 6.1% to 12.9% in Gyeonggi, which implies that a lower number of transfer users has a positive effect on housing prices in Seoul unlike Gyeonggi. It also is noteworthy that the distance to the urban railway station had a negative effect on housing prices in Seoul and positive effect in Gyeonggi. Taking these results together, in Seoul, the increase in the number of transit users had a negative effect on neighborhood housing prices. When analyzed by segments, however, an additional negative effect was observed only in the apartments located within the radius of 100 meters. It is also found that the impact of transit users varies according to the regional characteristics, such as the density of commercial facilities and the population density, and the spatial extent of negative effect also showed regional differences. These results provide implications for the planning of new stations, new cities, and land use of existing areas around stations.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Spatial Information Research
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• v.9 no.1
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• pp.107-124
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• 2001

The purpose of this research is to develop system and to establish methodology for managing spatial Database in Land Management Information System(LMIS). Spatial Database which is used by a various public department such as parcel survey and registry, land use planning and Land value appraisal in local government, is composed of parcel map, topographic map and zoning map. Spatial data has been constructed and managed by various department and then hard to maintain accuracy and coinsistency. So, it is important to establish the basic data management concept that source data(ex : parcel map, topographic map, zoning map, etc.) should be managed by responsible department. at the same time, application data for bussiness (ex : individual parcel price map) must be recomposed from base map by it's own objects. This is, Spatial data management system (SDMS) should be designed, developed according to this concept for managing consistency among data, reducing construction and management cost of database. Our SDMS was developed based on Open LMIS middleware architecture using OpenGIS CORBA specification for standard interface, RUP(Rational Unified Process) for development methodology, UML(Unified Modeling Language) for system design and VisiBroker, C++, CAD system for system implementation.

• The Journal of Fisheries Business Administration
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• v.23 no.2
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• pp.101-128
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• 1992

How to distribute fisheries catches from producer to consumer is very important for everybody joined fisheries marketing channels (FMC), because most people are influenced their revenue and expenditure through marketing channels. Many institutions in Korea after 1960's have tried to develop the rationalization of FMC, but they have not gotten the satisfactory results in general in spite of a lot fruits. Comparing with general manufacturing industry, the fisheries industry has some specializations in the marketing channels. It makes them unique structure included wholesale market system similiar to fresh (perishable) food market with expertised technology. Wholesale market collects, distributes the fisheries catches and evaluates in by auction or bidding without consideration of producer's opinion. It is very necessary institution to make a decision to equatible price for fresh food and to play an important role for marketing effectiveness with minimum total transation and with massed reserve among institutions. But it has two weak points to increase the marketing cost and to make products bad fresh (perishable). Therefore, both Producer and consumer want to find the direct channels not to pass through wholesale market and to get more profit. I wanted to explain what problems of traditional FMC are and why the direct channel is necessary as follows in this paper. Chapter II : The types and specialization of FMC Chapter III : The structure and problem of fisheries wholesale market channel Chapter IV Marketing cost of FMC and direct channel I suggested when the direct channel in FMC is designed, new planner must carry out marketing functions which are performanced by wholesaler, middle man and the joined members of auction at wholesale market. In view of consumption area, these functions are : (1) the finding of production partner to make a business ; (2) communication of information ; (3) collecting ; (4) distribution ; (5) selecting and grading ; (6) evaluating ; (7) financing and payment ; (8) organization, in view of consumption area. The government must support also the group or individual of new direct channels to succeed it with (1) furnishing of market information (2) supplying of land and facility (3) financing (4) feed-back of dierct channels totally (5) making an opportunity of communication between producer and consumer. I want to emphasize again wholesale market is necessary and important institution for equatible price of fresh food in spite of the its weak points. At the same time. the direct channels are necessary to reduce the marketing cost and to keep better fresh food.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.310-321
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• 2021

The influence of regional economic growth on migration may also differ by age and generation age due to individual lifestyle. Therefore, this study analyzes an effects of changes in regional economic growth on migration between regions by age group. The result shows that the increase in the growth rate of the regional economy and job creation increased the net migration rate, regardless of age group. Second, it is found that the growth rate of the regional economy and job creation have a greater effect on the net migration rate for the youth population than for the middle-aged group. Third, it is found that the gap between regions in the level of individual income in the 25 to 29 years old and the level of land price fluctuations in the 40 to 64 years old affect the net migration rate. This implies that regional economic growth is still an important factor in the migration between regions, and has a great influence on the youth population.

• Journal of the Korean association of regional geographers
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• v.16 no.1
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• pp.34-47
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• 2010

The purpose of this study is to investigate the actual condition of commercial use of housing site in residential development complexes, and to derive effective future development plan by analyzing the influence of penetrating factors of commercial use. The foJlowing are the results of the analysis. First, characteristics of roads showed that the wider the widths of roads adjoining individual lots have more influences on commercial use penetration. This means that non-residential facilities tend to be located on regions where frequencies of uses are high, preferring regions having good transportation accessibility. Second, characteristics of adjacent usage showed that the distances of common housing, neighborhood facilities, schools to single-detached residential units acted as a factor for higher penetration ratio of commercial use when they were closer.ors an opposite, it showed as distances to parks were further, the penetration ratio were higher. This can be inferred that the condition of detached houses located closer to parks have pleasure environment, and act as a factor preventing commercial use penetration. Third, the official land price presents as a form of quality, as the analysis showed that the higher official land price, the more it acts as a factor increasing the penetration ratio of commercial use.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.5-21
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• 2019

The purpose of this study is to investigate and analyze the cadastral transformation process of Dokdo-ri based on the institutional concept of the cadastre, while presenting the cadastral characteristics of Dokdo-ri therefrom. For this purpose, both the literature search method and the Internet search method were used. As for the analysis method, descriptive analysis method and comparative analysis method were used. The findings support that the cadastral characteristics of Dokdo-ri is drawn as follows: First, from the physical point of view, the cadastral characteristics of Dokdo-ri shows that the territory is given by the smallest lot numbers in the country and that the territory is also given by the land lot number consisting of small size lots without continuing the ground for which the cadastral resurvey project was carried out for the first time. Second, in terms of the rights, the cadastral characteristics of Dokdo-ri shows that the entire area given by the lots is owned by a single owner and no ownership has been changed. Third, in terms of its value, the cadastral characteristics of Dokdo-ri shows that it is the only area given by the lots of which the officially assessed individual land price has never been decreased in the entire lots. Fourth, when it comes to presenting the cadastral characteristics of Dokdo-ri in terms of the use control/restriction, the consciousness of preserving Dokdo-ri and the consciousness of enhancing real territory are confronted but due to the Cultural Heritage Protection Act etc, the cadastre turned out to be a very passive cadastral work.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• Journal of the Korean Geographical Society
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• v.38 no.5
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• pp.667-685
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• 2003

To address the requirements of gap analysis for species protection, as well as the needs of state and federal agencies for detailed digital land cover, a 43-class map at the vegetation alliance level was created for the state of Kansas using multi-temporal Thematic Mapper imagery. The mapping approach included the use of three-date multi-seasonal imagery, a two-stage classification approach that first masked out cropland areas using unsupervised classification and then mapped natural vegetation with supervised classification, visualization techniques utilizing a map of small multiples and field experts, and extensive use of ancillary data in post-hoc processing. Accuracy assessment was conducted at three levels of generalization (Anderson Level I, vegetation formation, and vegetation alliance) and three cross-tabulation approaches. Overall accuracy ranged from 51.7% to 89.4%, depending on level of generalization, while accuracy figures for individual alliance classes varied by area covered and level of sampling.

• Journal of the Korean Regional Science Association
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• v.32 no.1
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• pp.67-82
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• 2016

This study aims to test the spatial mismatch hypothesis by exploring the relationship between income and commuting time in Seoul, Korea. For this purpose, we analyze the commuting times of individuals who commute to Seoul, using the data for the metropolitan household survey. We employed a hierarchial linear model(HLM) to capture the effects of both individual attributes and regional attributes, and their interactions. The results show that the commuting time decreases with household income controlling for the regional attributes, and the effect of income increases with the housing price of the location of a commuter's firm. This implies that the spatial mismatch holds for Seoul as follows: Lower personal income and housing affordablility extend individuals' commuting times, and the destinations' characteristics such as housing type and land use also have impacts on commuting time. These results have some policy implications for achieving social equity in terms of spatial structure of the city.