• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.105-120
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• 1997

One of the most important issues of object-oriented geographical database system is to develop an indexing technique which enables more efficient I/O processing within aggregation hierarchy or inheritance hierarchy. Up to present, several indexing schemes have been developed for this purpose. However, they have separately focused on aggregation hierarchy or inheritance hierarchy of object-oriented data model. A recent research is proposing a nested-inherited index which combines these two hierarchies simultaneously. However, this new index has some weak points. It has high storage costs related to its use of auxiliary index. Also, it cannot clearly represent the inheritance relationship among classes within its index structure. To solve these problems, this thesis proposes a pointer-chain index. Using pointer chain directory, this index composes a hierarchy-typed chain to show the hierarchical relationship among classes within inheritance hierarchy. By doing these, it could fetch the OID list of objects to be retrieved more easily than before. In addition, the pointer chain directory structure could accurately recognize target cases and subclasses and deal with "select-all" typed query without collection of schema semantic information. Also, it could avoid the redundant data storing, which usually happens in the process of using auxiliary index. This study evaluates the performance of pointer chain indexing technique by way of simulation method to compare nested-inherited index. According to this simulation, the pointer chain index is proved to be more efficient with regard to storage cost than nested-inherited index. Especially in terms of retrieval operation, it shows efficient performance to that of nested-inherited index.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.122-131
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• 2004

Traditional works on indexing have been suggested for low dimensional data under dynamic environments. But recent database applications require efficient processing of huge sire of high dimensional data under static environments. Thus many indexing strategies suggested especially in partitioning ones do not adapt to these new environments. In our study, we point out these facts and propose a new partitioning strategy, which complies with new applications' requirements and is derived from analysis. As a preliminary step to propose our method, we apply a packing technique on the one hand and exploit observations on the Minkowski-sum cost model on the other, under uniform data distribution. Observations predict that unbalanced partitioning strategy may be more query-efficient than balanced partitioning strategy for high dimensional data. Thus we propose our method, called CSP (Cyclic Spliced Partitioning method). Analysis on this method explicitly suggests metrics on how to partition high dimensional data. By the cost model, simulations, and experiments, we show excellent performance of our method over balanced strategy. By experimental studies on other indices and packing methods, we also show the superiority of our method.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.195-204
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• 2004

The Semantic Web is proposed as the next generation Web technology. In the environment of the Semantic Web, resources are related with each other semantically and computers can process this information easily. The Resource Description Framework (RDF) supports this semantic relationship. RDF is the data model for describing metadata of the Web resources. To establish and develop the Semantic Web, methods for managing RDF data efficiently are the most important. So, in this research, we propose methods for storing and querying RDF data using an XML database system. Using an XML database system, XML data, main data of the Semantic Web, and RDF data, the metadata of XML data, can be managed in the same storage and by the same mechanism efficiently. In addition, we propose an efficient data retrieval method and several techniques to improve the system performance. Our query processing technique performs better than an existing system.

• Journal of KIISE
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• v.43 no.2
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• pp.237-245
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• 2016

In this paper we introduce a novel database research area called science of databases (SoDB) and carry out a comprehensive analysis of its case studies. SoDB aims to better understand interesting phenomena observed across multiple database management systems (DBMSes). While mathematical and engineering work in the database field has been dominant, less attention has been given to scientific approaches through which DBMSes can be better understood. Scientific investigations can lead to better engineered designs through deeper understanding of query optimizers and transaction processing. The SoDB research has investigated several interesting phenomena observed across different DBMSes and provided several engineering implications based on our uncovered results. In this paper we introduce a novel scientific, empirical methodology and describe the research infrastructure to enable the methodology. We then review each of a selected group of phenomena studied and present an identified structural causal model associated with each phenomenon. We also conduct a comprehensive analysis on the case studies. Finally, we suggest future directions to expand the SoDB research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1676-1689
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• 2014

At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users' interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points' neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.1-10
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• 2009

One important issue to generalize the ubiquitous paradigm is the development of user-centralized and intelligent ubiquitous computing systems. Sharing knowledge and correct communication between users and devices are needed to be aware of continuous changed context information and infer services for which users are suited. The goal of this paper is to describe and manage effectively the meaning of services or data which each device offers for interaction between users and devices based on semantic relationships and reasoning. In this paper, we represent semantic data using OWL and design a ubiquitous based intelligent system. We propose some index structures and strategies to process queries classified by each subsystem and adopt labeling schemes to identify classes and resources in the semantic data. We can find devices which satisfies various user's requests exactly and quickly using the proposed strategies.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.141-150
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• 2008

In this mobile computing environment, data broadcasting is widely used to resolve the problem of limited power and bandwidth of mobile equipments. Most previous broadcast indexing methods concentrate on flat data. However. with the growing popularity of XML, an increasing amount of information is being stored and exchanged in the XML format. We propose a novel indexing method. called TOP tree(Tree Ordering based Path summary tree), for indexing XML document on mobile broadcast environments. TOP tree is a path summary tree which provides a concise structure summary at group level using global IDs and element information at local level using local IDs. Based on the TOP tree representation, we suggest a broadcast stream generation and query Processing method that efficiently handles not only simple Path queries but also multiple path queries. We have compared our indexing method with other indexing methods. Evaluation results show that our approaches can effectively improve the access time and tune-in time in a wireless broadcasting environment.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.38-43
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• 2016

Recent developments regarding transportation technology have positioned travel as a major leisure activity; however, trip-itinerary planning remains a challenging task for tourists due to the need to select Points of Interest (POI) for visits to unfamiliar cities. Meanwhile, due to the GPS functions on mobile devices such as smartphones and tablet PCs, it is now possible to collect a user's position in real time. Based on these circumstances, our research on an automatic itinerary-planning system to simplify the trip-planning process was conducted briskly. The existing studies that include research on itinerary schedules focus on an identification of the shortest path in consideration of cost and time constraints, or a recommendation of the most-popular travel route in the destination area; therefore, we propose a personalized itinerary-recommendation system for which the stay-time preference of the individual user is considered as part of the personalized service.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.167-178
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• 2003

In mobile computing environments, queries based on the location of mobile clients (MCs) may cause different results. We say that the data of these results are location dependent data (LDD). Location-dependent queries to LDD need to be processed in conjunction with the geographical distance. The efficiency of query processing may also be increased by LDD relationship, etc. But there is the problem of fuzziness about how the distance used in location-dependent queries is evaluated and the data regions are organized. In this paper, we quantify the fuzziness of a location-dependent fuery on LDD. And we propose data regions for LDD, called LDD regions, by relationship of accessed data and the degree of distance between data objects and MCs' locations. In simulation studies we show that the number of database access for location-dependent queries, which have several settings on MCs' favor and two granularity of regions, can be smaller in proposed LDD regions than that in geographical regions.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.52-62
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• 2015

As a recent dominant web trend, mobile first strategy has been emphasized, and interests with respect to responsive web that provides effective methodology to various mobile devices and their display resolution are also increasing. However, it is an early adoption stage in web mapping for geo-spatial applications. This study is to present some practical examples of layouts using responsive web technologies linked to geo-spatial open platform. Suggestive consideration points for further application of responsive web to geo-spatial services are presented. On test implementing, HTML5, JavaScript, and CSS3 were used, and web mapping processing using OpenLayers was performed. It is expected that responsive web applications for contents derived from geo-spatial information or location data increase.