• Journal of Korea Society of Industrial Information Systems
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• v.9 no.1
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• pp.77-84
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• 2004

Recently, as the number of entities participating in the Grid system increased, the response time of LDAP system became inadequate. Consequently, we have to design new LDAP that suitable for high performance Grid environments. For this, researches about analysis of performance LDAP system are needed firstly. However, because researches are focused mostly on read operation optimized environments, so these result of researches are not directly applied to high performance Grid environments that write operation occupies most. In this paper, we provide overall results of analysis of performance of LDAP system with respect to number of node, query arrival rate, probability of read and so on. The analysis is based on in analytic performance model by applying the M/M/1 queuing model. Finally, based on the results, we suggest the direction for the design of high performance LDAP system and this research results can be applied as basic materials to design of GIS in high performance Grid environments as well as.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.476-493
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• 2003

Data broadcast is an effective data transmission method from a data base server to numerous mobile clients due to the restrictions on mobile environment such as low wireless communication bandwidth and energy shortage of mobile devices. There are various broadcast methods based on clients' data access frequencies or semantic relationship of data. The broadcast schedule based only on the access frequencies does not consider semantic relations of data, so that when a client needs to access a series of semantically related data, the client has to listen to the wireless channel for a long time. On the other hand, the broadcast schedule based only on semantic relationship of data makes data access time longer when clients highly request specific data which are not semantically related but frequently accessed. In this paper, we present an efficient data broadcast method based on not only data access frequencies but also semantic relationship to improve mobile clients' query response time. The new hybrid broadcast method we propose creates a data broadcast schedule according to the data access frequencies and then the schedule is adjusted to reflect semantic relationship of data. We show our method is efficient by experimental performance analysis.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.127-133
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• 2019

SQL is the most common language in data processing. Therefore, most of the colleges offer SQL in their curriculum. In this research, an auto scoring SQL test is proposed for the efficient results of SQL education. The system was treated with algorithms instead of using expensive DBMS(Data Base Management System) for automatic scoring, and satisfactory results were produced. For this system, the test question bank was established out of 'personnel management' and 'academic management'. It provides users with different sets of test each time. Scoring was done by dividing tables into two sections. The one that does not change the table(select) and the other that actually changes the table(update, insert, delete). In the case of a search, the answer and response were executed at first and then the results were compared and processed, the user's answers are evaluated by comparing the table with the correct answer. Modification, insertion, and deletion of table actually changes the data table, so data was restored by using ROLLBACK command. This system was implemented and tested 772 times on the 88 students in Computer Information Division of our college. The results of the implementation show that the average scoring time for a test consisting of 10 questions is 0.052 seconds, and the performance of this system is distinguished considering that multiple responses cannot be processed at the same time by a human grader, we want to develop a problem system that takes into account the difficulty of the problem into account near future.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.115-122
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• 2002

This paper presents a new web cluster scheme based on dispatcher which does not depend on operating system for server and can examine server's status interactively. Two principal functions are proposed for new web cluster technique. The one is self-controlled load distribution and the other is transaction fail-safe. Self-controlled load distribution function checks response time and status of servers periodically, then it decides where the traffic goes to guarantee rapid response for every query. Transaction fail-safe function can recover lost queries including broken transaction immediately from server errors. Proposed new web cluster scheme is implemented by C language on Unix operating system and compared with legacy web cluster products. On the comparison with broadcast based web cluster, proposed new web cluster results higher performance as more traffic comes. And on the comparison with a round-robin DNS based web cluster, it results similar performance at the case of traffic processing. But when the situation of one server crashed, proposed web cluster processed traffics more reliably without lost queries. So, new web cluster scheme Proposed on this dissertation can give alternative plan about highly increasing traffics and server load due to heavy traffics to build more reliable and utilized services.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

• Asia pacific journal of information systems
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• v.19 no.1
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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.