• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.488-496
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• 2004

This paper describes a music information retrieval system which uses humming as the key for retrieval Humming is an easy way for the user to input a melody. However, there are several problems with humming that degrade the retrieval of information. One problem is a human factor. Sometimes people do not sing accurately, especially if they are inexperienced or unaccompanied. Another problem arises from signal processing. Therefore, a music information retrieval method should be sufficiently robust to surmount various humming errors and signal processing problems. A retrieval system has to extract pitch from the user's humming. However pitch extraction is not perfect. It often captures half or double pitches. even if the extraction algorithms take the continuity of the pitch into account. Considering these problems. we propose a system that takes multiple pitch candidates into account. In addition to the frequencies of the pitch candidates. the confidence measures obtained from their powers are taken into consideration as well. We also propose the use of an algorithm with three dimensions that is an extension of the conventional DP algorithm, so that multiple pitch candidates can be treated. Moreover in the proposed algorithm. DP paths are changed dynamically to take deltaPitches and IOIratios of input and reference notes into account in order to treat notes being split or unified. We carried out an evaluation experiment to compare the proposed system with a conventional system. From the experiment. the proposed method gave better retrieval performance than the conventional system.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.455-462
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• 2006

Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1265-1275
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• 2002

In the network management system, there are two approaches; the centralized approach based on SNMP and the distributed approach based on mobile agent. Some information changes with time and the manager needs to monitor its value in real time. In such a case, the polling is generally used in SNMP because the manager can query agents periodically. However, the polling scheme needs both request and response messages for management information every time, which results in network traffic increase. In this paper, we suggest an adaptive network monitoring method to reduce the network traffic for SNMP-based network management. In the proposed strategy, each agent first decides its on monitoring period. Then, the manager collects them and approves each agent's period without modification or adjusts it based on the total traffic generated by monitoring messages. After receiving response message containing monitoring period from the manager, each agent sends management information periodically without the request of manager. To evaluate performance of the proposed method, we implemented it and compared the network traffic and monitoring quality of the proposed scheme with the general polling method.

• 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.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.

• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.425-430
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• 2007

Without the aid of stationary infrastructure, maintaining routing information for all nodes is inefficient in the Mobile Ad hoc Networks(MANET). It is more efficient when every time routing information is necessary that the source node broadcasts a query message to neighbour nodes. The source node using Ad hoc On-Demand distance Vector(AODV), which is one of the routing protocols of MANET, uses the Expanding Ring Search(ERS) algorithm which finds a destination node efficiently. In order to reduce the congestion of the network, ERS algorithm does not broadcast Route REQuest(RREQ) messages in the whole network. When the timer expires, if source node does not receive Route REPly(RREP) messages from the destination node, it gradually increases TTL value and broadcasts RREQ messages. Existing AODV cost a great deal to find a destination node because it uses a fixed NODE_TRAVERSAL_TIME value. Without the message which is added in existing AODV protocols, this paper measures delay time among the neighbours' nodes by making use of HELLO messages. We propose Adaptive ERS(AERS) algorithm that makes NET_TRAVERSAL_TIME optimum which apply to the measured delay time to NODE_TRAVERSAL_TIME. AERS suppresses the unnecessary messages, making NET_TRAVERSAL_TIME optimum in this paper. So we will be able to improve a network performance. We prove the effectiveness of the proposed method through simulation.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.180-192
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• 2000

Recently, the component technology has played a main role in software reuse. It has changed the code-based reuse into the binary code-based reuse, because components can be easily combined into the developing software only through component interfaces. Since components and component users have increased rapidly, it is necessary that the users of components search for the most proper components for HTML among the enormous number of components on the Internet. It is desirable to use web-document-typed specifications for component specifications on the Internet. This paper proposes to use XML component specifications instead of HTML specifications, because it is impossible to represent the semantics of contexts using HTML. We also propose the XML context-search method based on XML component specifications. Component users use the contexts for the component properties and the terms for the values of component properties in their queries for searching components. The index structure for the context-based search method is the inverted file indexing structure of term-context-component specification. Not only an XML context-based search method but also a variety of search methods based on context-based search, such as keyword, search, faceted search, and browsing search method, are provided for the convenience of users. We use the 3-layer architecture, with an interface layer, a query expansion layer, and an XML search engine layer, of the search engine for the efficient index scheme. In this paper, an XML DTD(Document Type Definition) for component specification is defined and the experimental results of comparing search performance of XML with HTML are discussed.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.179-192
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• 2007

This paper addresses an approach that recommends investment types for stock investors by discovering useful rules from past changing patterns of stock prices in databases. First, we define a new rule model for recommending stock investment types. For a frequent pattern of stock prices, if its subsequent stock prices are matched to a condition of an investor, the model recommends a corresponding investment type for this stock. The frequent pattern is regarded as a rule head, and the subsequent part a rule body. We observed that the conditions on rule bodies are quite different depending on dispositions of investors while rule heads are independent of characteristics of investors in most cases. With this observation, we propose a new method that discovers and stores only the rule heads rather than the whole rules in a rule discovery process. This allows investors to define various conditions on rule bodies flexibly, and also improves the performance of a rule discovery process by reducing the number of rules. For efficient discovery and matching of rules, we propose methods for discovering frequent patterns, constructing a frequent pattern base, and indexing them. We also suggest a method that finds the rules matched to a query issued by an investor from a frequent pattern base, and a method that recommends an investment type using the rules. Finally, we verify the superiority of our approach via various experiments using real-life stock data.

• 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.