• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.397-400
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• 2010

우리는 지난 연구에서 변형 비속어 필터링 시스템을 위하여 근사 문자열 검색 시스템을 적용하여 서열 정렬 횟수를 비약적으로 줄일 수 있었다. 다차원 데이터 구조를 이용한 한글 근사 검색 시스템은 기준축인 Base-Pivot의 숫자에 따라 검색 결과의 정확도를 높일 수 있으나 BP이 증가한 만큼 질의 단어의 좌표를 계산하기 위한 시간이 오래 걸린다. 소규모 데이터 검색에는 문제가 되지 않으나 60,000단어 이상의 데이터가 수록되는 국어사전과 같은 대규모 데이터를 검색하게 될 경우 요구되는 BP의 숫자도 증가하여 많은 연산시간을 필요로 한다. 본 논문에서는 기존의 근사 단어 검색 시스템을 계층구조화 하여 요구되는 BP 숫자를 감소 시켜 성능을 향상 시키는 방법을 제안하고자 한다. 그리고 실험을 통하여 본 아이디어의 실효성을 증명하였다. 본 아이디어는 기존의 6000개의 비속어에 대하여 약 20%정도의 성능향상을 보였다.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.1-17
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• 2007

As XML is becoming a de facto standard for distribution and sharing of information, the need for an efficient yet secure access of XML data has become very important. To enforce the fine-level granularity requirement, authorization models for regulating access to XML documents use XPath which is a standard for specifying parts of XML data and a suitable language for both query processing. An access control environment for XML documents and some techniques to deal with authorization priorities and conflict resolution issues are proposed. Despite this, relatively little work has been done to enforce access controls particularly for XML databases in the case of query access. Developing an efficient mechanism for XML databases to control query-based access is therefore the central theme of this paper. This work is a proposal for an efficient yet secure XML access control system. The basic idea utilized is that a user query interaction with only necessary access control rules is modified to an alternative form which is guaranteed to have no access violations using tree-aware metadata of XML schemes and set operators supported by XPath 2.0. The scheme can be applied to any XML database management system and has several advantages over other suggested schemes. These include implementation easiness, small execution time overhead, fine-grained controls, and safe and correct query modification. The experimental results clearly demonstrate the efficiency of the approach.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.56-61
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• 2012

Several Visualization techniques have been applied in traffic information area. This work is the basic research for applying of interactive visualization techniques when the traffic information is provided to users. Design of interactive visualization techniques were applied to traffic information services. Previous studies for information visualization with interactive visualization techniques were investigated, and the traffic information services currently provided were analyzed. There are many types of interactive visualization techniques, but this study is mainly focused on selecting, querying, linking, filtering and rearranging techniques. The users can obtain the proper and more suitable information for theie needs, because each interactive visualization techniques support interaction between information and users. The traffic information which has one of interactive techniques can be more effective for decision making and utilization. More attention is given to interactive visualization of data and information techniques in transportation field. By this research, it is expected that traffic information services is more effective and can be a foundation work for various interactive visualization techniques in traffice inforamtion.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.1
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• pp.38-46
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• 2009

With the rapid increase in the number of Web documents, the problem of information overload is growing more serious in Internet search. In order to ease the problem, researchers are paying attention to personalization, which creates Web environment fittingly for users' preference, but most of search engines produce results focused on users' queries. Thus, the present study examined the method of producing search results personalized based on a user's understanding level. A characteristic that differentiates this study from previous researches is that it considers users' understanding level and searches documents of difficulty fit for the level first. The difficulty level of a document is adjusted based on the understanding level of users who access the document, and a user's understanding level is updated periodically based on the difficulty of documents accessed by the user. A Web search system based on the results of this study is expected to bring very useful results to Web users of various age groups.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.1-9
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• 2012

The popularity of digital music and smart phones led to develope noise-robust real-time audio fingerprinting system in various ways. In particular, The Multiple Hashing(MLH) of fingerprint algorithms is robust to noise and has an elaborate structure. In this paper, we propose a filter engine based on MLH to achieve better performance. In this approach, we compose a energy-intensive filter to improve the accuracy of Q/R from music database and a statistic filter to remove continuity and redundancy. The energy-intensive filter uses the Discrite Cosine Transform(DCT)'s feature gathering energy to low-order bits and the statistic filters use the correlation between searched fingerprint's information. Experimental results show that the superiority of proposed algorithm consists of the energy and statistical filtering in noise environment. It is found that the proposed filter engine achieves more robust to noise than Philips Robust Hash(PRH), and a more compact way than MLH.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.123-140
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• 2009

Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.459-470
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• 2003

It is required to research on high-dimensional index structures for efficiently retrieving high-dimensional data because an attribute vector in data warehousing and a feature vector in multimedia database have a characteristic of high-dimensional data. For this, many high-dimensional index structures have been proposed, but they have so called ‘dimensional curse’ problem that retrieval performance is extremely decreased as the dimensionality is increased. To solve the problem, the cell-based filtering (CBF) scheme has been proposed. But the CBF scheme show a linear decreasing on performance as the dimensionality. To cope with the problem, it is necessary to make use of parallel processing techniques. In this paper, we propose a parallel CBF scheme which uses a horizontally-partitioned technique as declustering. In order to maximize the retrieval performance of the proposed parallel CBF scheme, we construct our parallel CBF scheme under a SN (Shared Nothing) cluster architecture. In addition, we present a data insertion algorithm, a rage query processing one, and a k-NN query processing one which are suitable for the SN cluster architecture. Finally, we show that our parallel CBF scheme achieves better retrieval performance in proportion to the number of servers in the SN cluster architecture, compared with the conventional CBF scheme.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.91-107
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• 2006

To handling the extreme situation that must manage positional information of a very large volume, at least millions of moving objects. A cluster-based sealable distributed computing system architecture, called the GALIS which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone, was proposed. In this paper, we proposed a valid time management and time-zone shifting scheme, which are essential in realizing the long-term location data subsystem of GALIS, but missed in our previous prototype development. We explain how to manage valid time of moving objects to avoid ambiguity of location information. We also describe time-zone shifting algorithm with three variations, such as Real Time-Time Zone Shifting, Batch-Time Zone Shifting, Table Partitioned Batch-Time Zone Shifting, Through experiments related with query processing time and CPU utilization, we show the efficiency of the proposed time-zone shifting schemes.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.545-554
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• 2006

Although the current Web search engines provide tremendous information, it is hard to find right information among the huge information. Users need to spend extra time to filter out unnecessary information. In order to overcome the limit of current Web search engines, Semantic Web was developed to provide efficient search, integration, and reuse of information by structuring semantic information from Web resources. In this paper, an elementary education contents retrieval system using Semantic Web is proposed. The proposed system emphasizes history contents that have high relevancy among data. For construction of the proposed system, ontology is proposed first for elementary study contents and ontology for historical contents is proposed for easy access to those contents using semantic relation among them. Based on the ontology, the proposed system is designed and implemented. The proposed system has the following characteristics. First, the system provides various query formats in detail so that search results can be refined efficiently. Second, the system presents only semantically information connected with key words or including key words using study contents ontology. Finally, the proposed system can increase study effects by presenting various contents that are related with query by users.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.