• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.125-133
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So intuitive fuzzy c-means(IFCM) clustering algorithm is applied to improve KNN, which is the KNN/IFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of IFCM based on signal to noise ratio(SNR). Then, the k RPs are classified into different clusters through IFCM based on SNR. Experimental results indicate that the proposed KNN/IFCM hybrid algorithm generally outperforms KNN, KNN/FCM, KNN/PFCM algorithm when the locations error is less than 2m.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.109-115
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• 2011

As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So artificial neural network(ANN) clustering algorithm is applied to improve KNN, which is the KNN/ANN hybrid algorithm presented in this paper. For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of ANN based on SNR. Then, the k RPs are classified into different clusters through ANN based on SNR. Experimental results indicate that the proposed KNN/ANN hybrid algorithm generally outperforms KNN algorithm when the locations error is less than 2m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.67-74
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• 2018

This study has proposed a methodology to detect suspicious facilities that occupy national and public land by using the cadastral and digital maps. First, we constructed a spatial database of national & public land based on the cadastral maps by linking its management ledger. Using the PNU (Parcel Number) code as a key field, the data managed by different institutions are integrated into a single spatial information DB (database) and then, the use or nonuse state of each parcel is confirmed on the cadastral map. Next, we explored the suspicious facilities that existed in the unused parcel by utilizing the digital topographical map. Then, the proposed methodology was applied for various regions and tested its feasibility. Through this study, it will be possible to improve the utilization of digital maps and to manage the national and public land efficiently and economically.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.407-413
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• 2013

For Ubiquitous service, there are some method researched. To IT convergence study tourism the convergence of IT and tourism in recent years has emerged as a discipline in the future. Tourist information is information about tourism products as tourists tourism decision-making needed to say. Information presented information anytime, anywhere, using a contact-type media, mobile and efficient tourist information content and generate content using Smart App store to the database is needed. This paper, by taking advantage of the Smart App Places to generate content and Smart Things to query, modify, search, tourism information, tourism policy and tourists can be analyzed, and the average inclination and these efficient tourism information content and that can be utilizedmodels are proposed. This u-Smart is a tourist information system. Build the biggest advantages of the meta-meta-model in real time by utilizing Smart App disposition of existing tourism information and tourist and tourism rating database. Helps to generate patterned by digital tourism policy tourism information content.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• Spatial Information Research
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• v.19 no.1
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• pp.73-82
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• 2011

Recently, demand for the use of cadastral map is increasing in both public and private area. To use cadastral map in web or mobile environment, construction of the multi-representation database(MRDB) that is the compressed into multiple scale from the original map data is recommended. In this study, the map generalization methodology for the cadastral map by applying overlay with topographic map and polygon generalization technique is suggested. This process is composed of three steps, re-constructing the network data of topographic map, polygon merging of parcel lines according to network degree, and applying line simplification techniques. Proposed methodologies are applied to the cadastral map in Suwon area. The result map was generalized into 1:5,000, 1:20,000, 1:100,000 scale, and data compression ratio was shown in 15% 8% 1% level respectively.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.237-243
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• 2018

Most of public underground facilities are installed under the ground, thus it is difficult to recognize the accurate location even with the drawings. Studies are conducted to understand exact position of underground facilities using augmented reality. However, in those studies, establishing of additional 3D object model database is needed when AR system is used at field. Because most of public underground facility information are established as 2 dimensional. In this study, AR system is developed as mobile application which can use original 2D underground facility data to transfer 3D AR data automatically without additional 3D database establishment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.119-122
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• 2005

RFID(Radio Frequency IDentification) is appearing by point technology by Ubiquitous environment of new paradigm and Logistics' application. But, RFID chip of this is high price and short bandwidth, low power and interference etc. can become technological problem. This is getting into obstacle in common use. Reader and tag, Embedded software etc.. that is accomplishing standardization is imported paying most expensive Royalty. This paper is RFID cognition system that use PDA in Ubiquitous environment to apply to Logistics system. RFID cognition system processes input/output of fundamental information attaching tag to Logistics of products. And RFID cognition system supports quick and correct and safe synthetic Logistics managerial system through construction of database. This can prove minimization and customer service of Logistics expense. RFID cognition system is advantage that can widen range of application to area that cognition system of existent fixing style can not do. Also, It can expect economical effect through inexpensive system construction.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.221-224
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• 2005

According as marine leisure industry has developed and the demand of leisure culture has increased rapidly, a desire about service which supply marine safety and connect marine information is enlarging. We wish tc develop contents of download form that supply geographic information of Electronic Navigational Chart(ENC) in the marine that is digitalized to carrying along terminal of WIPI base and various informations for marine leisure. For this, DB that offer ENC and additional information should be constructed. Also, we need server (CPS; Contents provider Server) that offer required contents. In this paper, we design web retrieval component which store request information to database. When consumer required necessary information through personal mobile device, CPS can inform that. So, we wish to develop web retrieval agent component that parse informations in various World Wide Webs, and store to database.