• Journal of KIISE:Databases
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• 제34권5호
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• pp.448-464
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• 2007

Location-Based Services (LBSs) provide results to queries according to the location of the client issuing the query. In LBS, techniques such as caching and prefetching are effective approaches to reducing the data transmission from a server and query response time. However, they can lead to cache inefficiency and network overload due to the client's mobility and query pattern. To solve these drawbacks, we propose a semantic prefetching (SP) scheme using prefetching segment concept and improved cache replacement policies. When a mobile client enters a new service area, called semantic prefetching area, proposed scheme fetches the necessary semantic information from the server in advance. The mobile client maintains the information in its own cache for query processing of location-dependent data (LDD) in mobile computing environment. The performance of the proposed scheme is investigated in relation to various environmental variables, such as the mobility and query pattern of user, the distributions of LDDs and applied cache replacement strategies. Simulation results show that the proposed scheme is more efficient than the well-known existing scheme for range query and nearest neighbor query. In addition, applying the two queries dynamically to query processing improves the performance of the proposed scheme.

• Journal of KIISE:Databases
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• 제31권4호
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• pp.432-443
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• 2004

As the XML data has been widely used in the Internet, it is necessary to store and retrieve the XML data by using DBMSs. However, relational DBMSs suffer from the model difference between graph structure of the XML data and table forms in relational databases. We propose an ORDBMS-based DTD-dependent XML data management system Xing. Xing stores XML data in a DTD-dependent form in an object database. Since the object database schema has a graph structure and supports multi-valued attributes, mapping from an XML data model and queries into an object data model and OQLs is a simple problem. For rapid storing of large quantities of the XML data, we use SAX parser with customized Xing-tree which requires a small memory space compared with the DOM-tree. Xing also returns the query result in an XML document form. We have implemented the Xing system on top of UniSQL object-relational DBMS for the validity checking and performance comparison. For XML genome data from GenBank, and experimental evaluation shows that Xing can provide significant performance improvement (maximum 10 times) compared with the relational approach.

• Journal of KIISE:Databases
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• 제32권1호
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• pp.56-70
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• 2005

The results of location-dependent queries(LDQ) generally depend on the current locations of query issuers. Many mechanisms, e.g. broadcast scheme, hoarding, or racking policy, have been developed to improve the system peformance and provide better services, which are specialized for LDQs. Considering geographical adjacency of data and characteristics oi target area, caching policy and broadcast scheme affect the overall performance in LDQ. For this reason, we propose both the caching policy and broadcast scheme, which these features are reflected in. Based on the adjacency of data in LDQ, our broadcast scheme use Hilbert curve to cluster data. Moreover, in order to develop the caching policy suitable for LDQ on urban area, we apply the moving distance of a MH(Mobile Host) to our caching policy We evaluate the performance of the caching policy measuring the workload of MHs and the correctness of LDQ results and the performance of the broadcast scheme measuring the average setup-time of MHs in our experiments. Finally, we expect that our caching policy Provides more correct answers when executing LDQ in focal cache and leads significant improvement of the performance of MHs. It also seems quite probable that our broadcast scheme leads improvement of battery life of the MH.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.578-581
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• 2007

For tracing tag locations, a trajectories should be modeled and indexed in radio frequency identification (RFID) systems. The trajectory of a tag can be represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that the tag stays in the reader is missing from the trajectory represented only as a point, we should extend the region of a query to find the tag that remains in a reader. In this paper, we propose an interval data model of tag's trajectory in order to solve the problem. Trajectories of tags are represented as two kinds of intervals; dynamic intervals which are time-dependent lines and static intervals which are fixed lines. We also show that the interval data model has better performance than others with a cost model

• Journal of KIISE:Computing Practices and Letters
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• 제15권3호
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• pp.154-166
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• 2009

Database query and reporting tools, OLAP tools and data mining tools are typical front-end tools in Business Intelligence environment which is able to support gathering, consolidating and analyzing data produced from business operation activities and provide access to the result to enterprise's users. Traditional reporting tools have an advantage of creating sophisticated dynamic reports including SQL query result sets, which look like documents produced by word processors, and publishing the reports to the Web environment, but data source for the tools is limited to RDBMS. On the other hand, OLAP tools and data mining tools have an advantage of providing powerful information analysis functions on each own way, but built-in visualization components for analysis results are limited to tables or some charts. Thus, this paper presents a system that integrates three typical front-end tools to complement one another for BI environment. Traditional reporting tools only have a query editor for generating SQL statements to bring data from RDBMS. However, the reporting tool presented by this paper can extract data also from OLAP and data mining servers, because editors for OLAP and data mining query requests are added into this tool. Traditional systems produce all documents in the server side. This structure enables reporting tools to avoid repetitive process to generate documents, when many clients intend to access the same dynamic document. But, because this system targets that a few users generate documents for data analysis, this tool generates documents at the client side. Therefore, the tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the report viewer in the client side. Also, this reporting tool has data structure for integrating data from three kinds of data sources into one document. Finally, most of traditional front-end tools for BI are dependent on data source architecture from specific vendor. To overcome the problem, this system uses XMLA that is a protocol based on web service to access to data sources for OLAP and data mining services from various vendors.

• Journal of KIISE:Computing Practices and Letters
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• 제14권5호
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• pp.467-471
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• 2008

With active research on Web ontology, various storages and query languages have been developed to store Web Ontology. As SPARQL usage increases and most of storages are based on relational data base, the necessity of SPARQL-to-SQL translation algorithm development becomes issued. Even though several translation algorithms have been proposed, there still remain the following problems. They do not support fully SPARQL clauses and they are dependent on a specific storage model. This paper proposes a new model to use a specific translation algorithm independently on storages.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제14권5호
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• pp.173-178
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• 2014

Smart devices linked to high speed networks enable us to obtain location dependent data at anywhere and anytime. In this environment, a wireless data broadcast system can deal with enormous data request from a great number of clients effectively. In order to set up an efficient wireless data broadcast system, various data scheduling and indexing schemes have been proposed. However, a simulation framework to evaluate the schemes is not reported yet. In this paper, we design and develop a simulation framework for a wireless data broadcast system. The developed simulation framework can evaluate quickly a wireless data broadcast system and has scalability to adopt various data scheduling and indexing schemes for wireless data broadcasting.

• The Transactions of the Korea Information Processing Society
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• 제6권4호
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• pp.1129-1135
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• 1999

isolated word recognition using the Dynamic Time warping algorithm has shown good recognition rate on speaker dependent environment. But, practically, since the searching time of the dynamic Time Warping algorithm is rapidly increased as searching data is increased. it is hard to implement. In the context-dependent-short-query system such as educational children's workbook on the Web, the number of responses to the specific questions is limited. Therefore, the searching space for the answers can be reduced depending on the questions. In this paper, low cost implementation method using DTW for the Web has been proposed. To cover the weakness of DTW, the searching space is reduced by the context. the searching space, depends on the specific questions, is chosen from interest searchable candidates. In the real implementation, the proposed method show better performance of both time and recognition rate.

• Asia pacific journal of information systems
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• 제19권1호
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Journal of KIISE
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• 제44권10호
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• pp.1112-1123
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• 2017

As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.