• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.185-193
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• 2010

With the emergence of ubiquitous computing era, various models for providing personalized service have been proposed, and, especially, several recommendation service schemes have been proposed to give tailored services to users proactively. However, the previous recommendation service schemes utilize a wide range of data without and filtering and consider the limited context-aware information to predict user preferences so that they are not adequate to provide personalized service to users. In this paper, we propose an adaptive recommendation service scheme which proactively provides suitable services based on the current context. We use accumulated interaction contexts (IC) between users and devices for predicting the user's preferences and recommend adaptive service based on the current context by utilizing clustering and collaborative filtering. The clustering algorithm improves efficiency of the recommendation service by focusing and analyzing the data that is collected from the locations nearby the users. Collaborative filtering guarantees an accurate recommendation, even when the data is insufficient. Finally, we evaluate the performance and the reliability of the proposed scheme by simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.1-10
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• 2012

Recent spatial information technology has brought innovative improvement in both efficiency and accuracy. Especially, airborne LiDAR system(ALS) is one of the practical sensors to obtain 3D spatial information. Constructing reliable 3D spatial data infrastructure is world wide issue and most of the significant tasks involved with modeling manmade objects. This study aims to create a test data set for developing automatic building modeling methods by simulating point cloud data. The data simulates various roof types including gable, pyramid, dome, and combined polyhedron shapes. In this study, a robust bottom-up method to segment surface patches was proposed for generating building models automatically by determining model key points of the objects. The results show that building roofs composed of the segmented patches could be modeled by appropriate mathematical functions and the model key points. Thus, 3D digitizing man made objects could be automated for digital mapping purpose.

• Korean Journal of Microbiology
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• v.46 no.1
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• pp.1-8
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• 2010

New technologies are providing unprecedented knowledge into microbial community structure and functions. Even though nucleic acid based approaches provide a lot of information, metaproteomics could provide a high-resolution representation of genotypic and phenotypic traits of distinct microbial communities. Analyzing the metagenome from different microbial ecosystems, metaproteomics has been applied to seawater, human guts, activated sludge, acid mine drainage biofilm, and soil. Although these studies employed different approaches, they elucidated that metaproteomics could provide a link among microbial community structure, function, physiology, interaction, ecology, and evolution. These approaches are reviewed here to help gain insights into the function of microbial community in ecosystems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.243-251
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• 2016

LiDAR data processing steps include noise removal, filtering, classification, segmentation, shape recognition, modeling, and quality assessment. This paper focuses on modeling and accuracy evaluation of 3D objects with curved surfaces. The appropriate modeling functions were determined by analyzing surface patch shape. Existing methods for modeling curved surface features require linearization, initial approximation, and iteration of the non-linear functions. However, proposed method could directly estimate the unknown parameters of the modeling functions. The results demonstrate feasibility of the proposed method. The proposed method was applied to the simulated and real building data of hemi-spherical and semi-cylindrical surfaces. The parameters and accuracy of the modeling functions were estimated. It is expected that the proposed method would contribute to automatic modeling of various objects.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.105-114
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• 2018

Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.12-22
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• 2014

This study was carried out to classify forest communities and to aggregate forest cover types for the complex and diversified natural forest areas of Hwangaksan, Bakseoksan, Deogyusan, and Jirisan in southern region of Baekdudaegan Mountains. The vegetation data were collected by point-centered quarter sampling method. Eight hundred fifty one sample points were subjected to cluster analysis to classify 18 forest communities, which were aggregated into 7 representative forest cover types on the basis of community similarity from composition of canopy species. They were mixed mesophytic forest cover type, the others deciduous forest cover type, Quercus variabilis-Quercus serrata cover type, Quercus mongolica cover type, Pinus densiflora cover type, Carpinus laxiflora cover type, and Abies koreana cover type. The Quercus mongolica cover type was most widely distributed in the study areas, and this cover type tended to occur in the place of higher altitude as latitude was getting lower. Mixed mesophytic forest and the others deciduous forest cover type were commonly distributed in the areas of valley, on the other hand, Quercus mongolica cover type and Pinus densiflora cover type tended to be distributed in the areas of ridge.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.33-40
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• 2003

Data mining plays an important role in a knowledge discovery process and various algorithms of data mining can be selected for the specific purpose. Most of traditional hierachical clustering methode are suitable for processing small data sets, so they difficulties in handling large data sets because of limited resources and insufficient efficiency. In this study we propose a hybrid neural networks clustering technique, called PPC for Pre-Post Clustering that can be applied to large data sets and find unknown patterns. PPC combinds an artificial intelligence method, SOM and a statistical method, hierarchical clustering technique, and clusters data through two processes. In pre-clustering process, PPC digests large data sets using SOM. Then in post-clustering, PPC measures Similarity values according to cohesive distances which show inner features, and adjacent distances which show external distances between clusters. At last PPC clusters large data sets using the simularity values. Experiment with UCI repository data showed that PPC had better cohensive values than the other clustering techniques.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.4
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• pp.149-154
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• 2014

A user should pick up relevant answers by himself from various search results when using user participation question answering community like Knowledge-iN. If refined answers are automatically provided, usability of question answering community must be improved. This paper divides questions in Q&A documents into 4 types(word, list, graph and text), then proposes summarizing methods for each question type using document statistics. Summarized answers for word, list and text type are obtained by question clustering and calculating scores for words using frequency, proximity and confidence of answers. Answers for graph type is shown by extracting user opinion from answers.

• Journal of Agricultural Extension & Community Development
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• v.21 no.3
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• pp.25-52
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• 2014

The purpose of this study was to examine the motives of tourists who visited ecotourism villages in Korea. A self-administered survey was obtained from 254 visitors in six ecotourism villages. As for the motivations of ecotourism village visitors, four factors ('relaxation', 'adventure', 'experience natural' and 'family togetherness') were extracted. Three distinct segments were identified based on the motivation : multipurpose seekers (45.3%), relaxation seekers (34.6%), family togetherness seekers (20.1%). Socio-demographic characteristics and tourism behaviors of each segmentation were also analyzed. The findings should be of interest to practitioners of ecotourism village marketing and operation.

• Korean Journal of Microbiology
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• v.28 no.4
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• pp.337-344
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• 1990

Slime sampless from 10 ratating biological contactor (RBC) plants in New Jersey were microscopically examined. Filamentous bacteria such as Type 1701, Type 0041, Type 021N, Nocardia, Beggiatoa, and Sphaerotilus, which are commonly present as suspended forms also were found in RBC slimes growing as attached forms. However, the abundance wwas much different from that of activated sludge. In RBC slimes, Beggiatoa was most frequently observed filamentous bacteria and Sphaerotilus, Type 0041, Type 1701, Type 021N and Nocardia were present in decreasing order of abundance. There were morphologically two different types of Behhiatia in RBC slimes. The statistical anaysis shows that filamentous bacterial poulations between the 100 cm inside and the outside the RBC were different in most cases with significant interactions between the location and stage.