• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.197-214
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• 2006

A Web-based environment has very various and heterogeneous users. The emphasis on their individual characteristics may make it hard to reach the general understanding of how they seek and use information on the Web. The purpose of this study is to find common patterns in information seeking behavior on the Web by analyzing a series of cognitive movement of users in interaction with the Web. Based on Dervin's concept and Timeline interview methodology, this study collected 37 Web experience descriptions from 21 respondents, which consisted of 302 steps. Findings addressed that Web information seeking behavior can be classified into seven types : Starting, Searching, Viewing/B row sing , Examining/comparing, Finding/compiling, Deciding/Acting, and Ending. Movement paths in the seven-type information seeking process showed that user's interaction with the Web was repeated and circulated at the Viewing/Browsing step and that information seeking behavior on the Web was multi-directional and non-linear.

• 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.

• Convergence Security Journal
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• v.8 no.4
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• pp.167-179
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• 2008

As ubiquitous technology develops, there are many studies to provide various contents proper to users through a mobile device. However, there is a limit of information provision due to a small user interface of a mobile device. This study proposes a system that can solve a problem and provide an intelligent agent model appropriate to a mobile environment and job information positively that an individual user is interested. It is composed of a personalization engine to monitor users' behavior patterns and a learning algorithm to provide information to a mobile device. Analysis shows that preferred job items are different by sex, age and education, while a region affects job searching significantly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.63-71
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• 2011

The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.67-74
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• 2002

A study on image searching and management techniques is actively developed by user requirements for multimedia information that are existing as images, audios, texts data from various information processing devices. If we can automatically detect and segment changing scenes from real-time image sequences, we can improve an effectiveness of image searching systems. In this paper, we propose cut detection techniques based on image color distribution and we evaluated its performance on various real-time image sequences. Results of experiments show that the proposed method are robust on various image patterns than color histogram method using statistical informations of images. Also, these methods can be used for cut detection on real-time image sequences.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.83-83
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• 2000

Recently, Vision system has being used all around industry. Sensor systems are used for Mark Reader, for example, optical scanning is proximity sensor system, have many disadvantages, such as, lacking user interface and difficulty to store original specimens. In contrast with this, Vision systems for Mark Reader has many advantages, including function conversion to achieve other work, high accuracy, high speed, etc. In this thesis, we have researched the development of Mark Reader by using a Vision system. The processing course of this s)'stem is consist to Image Pre-Processing such as noise reduction, edge detection, threshold processing. And then, we have carried out camera calibration to calibrate images which are acquired from camera. After searching for reference point within scanning area(60pixe1${\times}$30pixe1), we have calculated points crossing by using line equations. And then, we decide to each ROI(region of interest) which are expressed by four points. Next we have converted absolute coordinate into relative coordinate for analysis a translation component. Finally we carry out Mark Reading with images classified by six patterns. As a result of experiment which follows the algorithm has proposed, we have get error within 0.5% from total image.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.1
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• pp.169-187
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• 1998

The primary purpose of this study is to compare printed index and abstract user's behaviours with digital index and abstract user's behaviours, and to verify of structured characteristics of a printed index and abstract. The major findings are as follows: (1) When the research topic is not specified enough, users tend to rely on printed indexes and abstracts search, whereas they utilize digital form in order to do retrospective search in the stage of research when the topic is determined. (2) Printed index and abstract users are expecting small number of literatures in search, whereas digital index and abstract users are expecting large number of literatures to be found The former are more satisfied with the result of search than the latter. (3) Digital index and abstract users experience more search failure than printed Index and abstract users. When they fail to find wanted materials, both users turn to the other form of indexes and abstracts. (4) Printed index and abstract users shows significantly less knowledge on online searching than digital index and abstract users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.619-626
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• 2012

With the service suggesting additional extended or related query, search engines aim to provide their users more convenience. The extended or related query suggestion service based on popularity, or by how many people have searched on web using the query, has limitations to elevate users' satisfaction, because each user's preference and interests differ. This paper will demonstrate the design and realization of the system that suggests extended query appropriate for users' demands, and also an improvement in the computing process between entering the first search word and the subsequent extension to the related themes. According to the evaluation the proposed system suggested 41% more extended or related query than when searching on Google, and 48% more than on Yahoo. Also by improving the shortcomings of the extended or related query system based on general popularity rather than each user's preference, the new system enhanced users' convenience further.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.898-905
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• 2005

Iris recognition Is that identifies a user based on the unique iris muscle patterns which has the functionalities of dilating or contracting pupil region. Because it is reported that iris recognition is more accurate than other biometries such as face, fingerprint, vein and speaker recognition, iris recognition is widely used in the high security application domain. However, if unnecessary information such as eyelid and eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate iris code including eyelash and eyelid, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelid by using pyramid searching parabolic deformable template. In addition, we detect the eyelash by using the eyelash mask. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.3\%$ compared to that not using it.