• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.7-18
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• 2012

It has been studied to support data having multiple properties, called Skyline Query. The skyline query is not exploring data having all properties but only meaningful data, when we retrieve informations in large data base. The skyline query can be used to provide some information about various environments and situations in sensor network. However, the legacy skyline query has a problem that increases the number of comparisons as the number of sensors are increasing in multi-dimensional data. Also important values are often omitted. Therefore, we propose a new method to reduce the complexity of comparison where the large number of sensors are placed. To reduce the complexity, we transfer a CMF(Category Based Member Function) which can identify preference of specific data when interest query from sync-node is transferred to sub-node. To show the validity of our method, we analyzed the performance by simulations. As a result, it showed that the time complexity was reduced when we retrieved information in multiple sensing data and omitted values are detected by great dominance Skyline.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.157-163
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• 2013

Data mining is a useful technology that can support new discoveries based on the pattern analysis and a variety of linkages between data, and currently is utilized in various fields such as finance, marketing, medical. In this paper, we propose an effective utilization method of data based on analysis of spatial data mining. We make use of basic data of foreigners living in Seoul. However, the data has some features distinguished from other areas of data, classification as sensitive information and legal problem such as personal information protection. So, we use the basic statistical data that does not contain personal information. The main features and contributions of the proposed method are as follows. First, we can use Big Data as information through a variety of ways and can classify and cluster Big Data through refinement. Second. we can use these kinds of information for decision-making of future and new patterns. In the performance evaluation, we will use visual approach through graph of themes. The results of performance evaluation show that the analysis using data mining technology can support new discoveries of patterns and results.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1386-1396
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• 2009

Most decision support functions of spatial data warehouse rely on the OLAP operations upon a spatial cube. Meanwhile, higher performance is always guaranteed by indexing the cube, which stores huge amount of pre-aggregated information. Hierarchical Dwarf was proposed as a solution, which can be taken as an extension of the Dwarf, a compressed index for cube structures. However, it does not consider the spatial dimension and even aggregates incorrectly if there are redundant values at the lower levels. OLAP-favored Searching was proposed as a spatial hierarchy based OLAP operation, which employs the advantages of R-tree. Although it supports aggregating functions well against specified areas, it ignores the operations on the spatial dimensions. In this paper, an indexing approach, which aims at utilizing the concept hierarchy of the spatial cube for decision support, is proposed. The index consists of concept hierarchy trees of all dimensions, which are linked according to the tuples stored in the fact table. It saves storage cost by preventing identical trees from being created redundantly. Also, it reduces the OLAP operation cost by integrating the spatial and aspatial dimensions in the virtual concept hierarchy.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.111-124
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• 2011

The apartment' share of the housing has steadily increased and property assets have been valued in importance as the one of asset value. Information retrieval system using internet is particularly active in the real estate market. However, user satisfaction on real estate information system is not very high, and there is a lack of research on real estate retrieval to increasing efficiency until now. This study presents a new knowledge information system developed to consider region-related factor and individual-related factor in the real estate market. In addition it enables a real estate knowledge system to search various preferential requirements for buyers such as school district, living convenience, easy maintenance as well as price. We made a survey of the search condition preference of experts on 30 real estate agents and then analyzed the result using AHP methodology. Furthermore, this research is to build apartment ontology using semantic web technologies to standardize various terminologies of apartment information and to show how it can be used to help buyers find apartments of the interest. After designing architecture of a real estate knowledge information system, this system is applied to the Busan real estate market to estimate the solutions of retrieval through Multi-Attribute Decision Making(MADM). Based on the results of the analysis, we endowed the buyer and expert's selected factors with weights in the system. Evaluation results indicate that this new system is to raise not only the value satisfaction of user, but also make it possible to effectively search and analyze the real estate through entropy analysis of MADM. This new system is to raise not only the value satisfaction of buyer's real estate, but also make it possible to effectively search and analyze the related real estate, consequently saving the searching cost of the buyers.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.145-154
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• 2016

Because of the recent interest in the u-Health and development of IT technology, a need of utilizing a medical information data has been increased. Among previous studies that utilize various data mining algorithms for processing medical information data, there are studies of association rule analysis. In the studies, an association between the symptoms with specified diseases is the target to discover, however, infrequent terms which can be important information for a disease diagnosis are not considered in most cases. In this paper, we proposed a new association rule mining system considering the importance of each term using TF-IDF weight to consider infrequent but important items. In addition, the proposed system can predict candidate diagnoses from medical text records using term similarity analysis based on medical ontology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2418-2423
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• 2012

A smart phone which is one of the new IT technologies can be viable on various enterprise applications since it provides easily information and services. Especially, a smart phone can request queries to a server which finds massive data for decision making and receive the results of the queries from the server. However, a smart phone has a drawback that its battery is consumed easily due to the 4G communication. In this paper, we propose mobile views in order to reduce the easy consumption of a battery on mobile client-server environment. The proposed mobile view scheme reduces the number of communication which is leading to power consumption using materialized views for processing queries. We also classify the methods to control the consistency of the mobile view as the sources of the view are changed and present the cost of each method based on the cost model of battery consumption.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.89-107
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• 2017

This study aims to compare information seeking behavior of 1300K users on PC and mobile phone. Transaction logs of 1300K, a major Korean shopping search engine, were analyzed. These transaction logs were collected over 1 month period, from April 1 to April 31, 2016. The results of this study show that there are a little more mobile sessions than PC sessions. Users conducted slightly more browsing on PCs than mobile phones, whereas users submitted queries more than two times on mobile phones than on PCs. Users clicked more search results on PCs than mobile phones, whereas users made important decision makings such as product purchases more on mobile phones than PCs. Top queries and categories were similar between PCs and mobile phones. Queries and categories on mobile phones were more focused than queries on PCs. Overall, mobile search behavior is more simple, passive, and focused than PC search behavior. The results of this study can be implemented to the effective improvement and development of search services for different devices.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.431-437
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• 2003

최근 국가산업 발달과 함께 자연 생EH계 파괴, 환경 오염 및 자연 훼손과 같은 문제점들이 야기되고 있으며, 범국가적인 차원에서 자연환경 보전과 관리에 대한 인식이 날로 부각되고 있다. 정보 시스템 분야에서도 다차원 지리정보를 이용한 자연 생태계 연구 및 환경오염원 관리와 같은 연구가 현재 활발하게 진행되고 있다. 이 논문은 자연환경과 생태계 관리를 위한 방법으로, 인터넷 GIS 기술을 이용한 지리정보 시스템을 구축하여 그 활용을 연구하였고, 연구 대상지로는 지리산 일대로 정하였으며, 환경의 범위는 자연환경 및 생태계로 정하였다. 공간정보 분석 및 관리를 위해 적지분석, 사용자 질의 처리 및 지리정보 가시화 모듈. 등을 개발하여 자연 환경정보를 보다 체계적으로 관리하기 위한 핵심 기능을 마련하였다. 각 모듈은 사용자 인터페이스를 제공하며, 특정 요구목적에 따라 공간분석을 통한 자연환경 및 생태계 접근에 대한 의사결정을 돕도록 하였다. 또한 환경상태 및 여러 목적에 따른 분류가 가능하도록 하여, 자연생태계, 야생 생물의 서식지를 보호 및 환경 오염원 관리분야의 활용할 수 있도록 하였다. 구현된 웹 기반 지리정보 시스템은 국립공원, 야생동물 보호 단체 및 환경단체를 통해 환경정보를 국민에게 제공하여 서비스의 질을 높일 수 있을 것으로 기대되며, 아울러 향후 생태계 보전 및 자연환경 보전연구에 기여할 것이다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.7-14
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• 2005

An OLAP(On-Line Analytical Processing) system is the decision support tool with which a user can analyze the information interactively in the various aspects. However, the traditional existing construction of an OLAP system has the inefficiency Problem of increasing the processing time and cost caused by the use of complex MDX(Multidimensional Expressions) queries. In an attempt to solve this problem, a new concept of data structuring technique, where a unit column whose elements are all 1 is added to the fact table, was suggested. With the data structuring technique, we can reduce the processing time and cost in OLAP systems.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.499-507
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• 2007

With the increasing of users' request about internet web service, importance of Internet datawarehouse to support decision making of users is increasing now. Early Internet datawarehouse was studied in the form of using existent database and XML. However, because of limitation of information expression ability, it is gradually changed to system that use metadata schema like RDFS. Because of distributed environment of the Internet, integration and saving of each metadata schemas into one global schema is important. However, between each different schema, semantic and structural conflicts can be happen in such situation and they must be controlled. In this paper, we analyze occasions of conflict when integrate distributed metadata schemas and propose conflict resolution technique for efficient internet datawarehouse query processing.