• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.113-121
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• 2009

In order to retrieve images with different emotions in regions of the images, this paper proposes the image retrieval system using emotion sketch. The proposed retrieval system divides an image into $17{\times}17$ sub-regions and extracts emotion features in each sub-region. In order to extract the emotion features, this paper uses emotion colors on 160 emotion words from H. Nagumo's color scheme imaging chart. We calculate a histogram of each sub-region and consider one emotion word having the maximal value as a representative emotion word of the sub-region. The system demonstrates the effectiveness of the proposed emotion sketch and our experimental results show that the system successfully retrieves on the Corel image database.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.483-494
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• 2001

Most of hypertext retrieval models consider documents as independent entities. They ignore relationships between documents of link semantics. in an information retrieval system for hypertext documents, retrieval effectiveness can be improved when ling information is used. Previous link-based hypertext retrieval models ignore link information while indexing. They utilize link information to re-rank the retrieval results. Therefore they are limited that only the documents is result-set utilize link information. This paper utilizes link information when indexing. We present how to use term weighting and inLinks weighting for ranking the relevant documents. Experimental results show that recall and precision evaluation according to the link semantics and the comparison with previously link_based hypertext retrieval model.

• Journal of the Korean Society for information Management
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• v.2 no.1
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• pp.96-107
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• 1985

The purpose of this study is to compare the retrieval effectiveness of KWIC index by automatic indexing method with Descriptor index by manual indexing method. The number of documents and requests used in this experimental study are 281 journal articles and 10 user requests in the area of nuclear engineering. The results of experiment show an average recall ratio of 54.89% for KWIC index and 64.42% for Descriptor index.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.87-93
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• 2012

This paper discusses a new weighting method for text analyzing from the view point of supervised learning. The term frequency and inverse term frequency measure (tf-idf measure) is famous weighting method for information retrieval, and this method can be used for text analyzing either. However, it is an experimental weighting method for information retrieval whose effectiveness is not clarified from the theoretical viewpoints. Therefore, other effective weighting measure may be obtained for document classification problems. In this study, we propose the optimal weighting method for document classification problems from the view point of supervised learning. The proposed measure is more suitable for the text classification problem as used training data than the tf-idf measure. The effectiveness of our proposal is clarified by simulation experiments for the text classification problems of newspaper article and the customer review which is posted on the web site.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.575-584
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• 2000

This paper presents a new image retrieval system with color and morphological informations based on binary sets. Each of them can be obtained from color binary sets and regional segmentation separately. For retrieval processes, the candidate images are decided by comparing color and their image binary sets of the database with query images. Particularly, it is possible that the retrieval of similar-measurements has a weight of color spatial distribution and its objective morphological features. We proposed a new idea for performing simply the complicated similar-measurement of candidated images to improve queried processes. The retrieval method using spatial and morphological features is shown with the effectiveness on the result of implementation on database with 3,000 images.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.91-96
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• 2014

Mobile image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes a new efficient and effective mobile image retrieval method that applies a weighted combination of color and texture utilizing spatial-color and second order statistics. The system for mobile image searches runs in real-time on an iPhone and can easily be used to find a specific image. To evaluate the performance of the new method, we assessed the iPhone simulations performance in terms of average precision and recall using several image databases and compare the results with those obtained using existing methods. Experimental trials revealed that the proposed descriptor exhibited a significant improvement of over 13% in retrieval effectiveness, compared to the best of the other descriptors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.610-618
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• 2002

This paper presents a new image retrieval method that is based on color space and block region information. The color space information of images can be obtained by color binary set, and the block region information can be obtained by regional segmentation and feature. The candidate images are decided by comparing with color features and its binary set of query image and image feature database for retrieval. Particularly, it is possible that the retrieval using similarity-measurements has the weights of color spatial distribution arid its objective block region features. This retrieval method using color spatial and block region features is shown with the effectiveness on the result of implementation on image database with 6,000 images.

• Journal of the Korean Society for Library and Information Science
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• v.26
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• pp.213-233
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• 1994

This study measured whether subject descriptor searching and citation searching retrieve different documents for conceptual queries and methodological queries in natural science, engineering and social science. The retrieval effectiveness of two search methods was measured using as criteria, total number of documents retrieved, total number of relevant documents, overlapping and unique documents and precision ratio. The search subject was water resources and the databases used were Selected Water Resources Abstracts (SWRA) and SCISEARCH. Data were collected for 21 doctoral students working on their dissertations in the three fields of water resources. Principal findings included: 1) subject searching and citation searching each retrieved substantially equal number of documents; 2) total number of relevant documents for conceptual queries was larger than that for methodological queries, while there was a large variation among the three fields; 3) the average overlap was quite small, while citation searching yielded more unique documents than subject searching; 4) for conceptual queries, citation searching yielded a higher precision ratio than subject searching, while subject searching obtained a slightly higher precision ratio than citation searching for methodological queries ; and 5) citation searching was effective for both specific queries and broad queries if seed articles are well chosen, while subject searching only worked well for broad queries. It was further found that: 1) citation searching is not a subsidiary but a substantial retrieval method in water resources; 2) SWRA is effective for queries for engineering and SCISEARCH is appropriate for queries for natural science, while neither SWRA nor SCISEARCH work well for queries for social science; and 3) characteristics of queries affect retrieval results more than the characteristics of documents or the coverage of databases.

• Restorative Dentistry and Endodontics
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• v.45 no.2
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• pp.14.1-14.7
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• 2020

Objective: The aim of this study was to perform a comparative evaluation of the effectiveness of ultrasonic tips versus the Terauchi file retrieval kit (TFRK) for the removal of broken endodontic instruments. Materials and Methods: A total of 80 extracted human first mandibular molars with moderate root canal curvature were selected. Following access cavity preparation canal patency was established with a size 10/15 K-file in the mesiobuccal canals of all teeth. The teeth were divided into 2 groups of 40 teeth each: the P group (ProUltra tips) and the T group (TFRK). Each group was further subdivided into 2 smaller groups of 20 teeth each according to whether ProTaper F1 rotary instruments were fractured in either the coronal third (C constituting the PC and TC groups) or the middle third (M constituting the PM and TM groups). Instrument retrieval was performed using either ProUltra tips or the TFRK. Results: The overall success rate at removing the separated instrument was 90% in group P and 95% in group T (p > 0.05) The mean time for instrument removal was higher with the ultrasonic tips than with the TFRK (p > 0.05). Conclusion: Both systems are acceptable clinical tools for instrument retrieval but the loop device in the TFRK requires slightly more dexterity than is needed for the ProUltra tips.

• Journal of the Korean Society for information Management
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• v.3 no.1
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• pp.70-102
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• 1986

This study is an attempt to develop a knowledge base with Inference mechanism for document retrieval, which is the core element of expert system. The purpose of this study is to design the knowledge base in order to intellectually process user queries eventually improving the effectiveness of information retrieval, under the assumption that the user who wants to search a certain subject generally lack the prior knowledge about that subject. In this paper, some characteristics of Korean complex nouns are structurally analyzed and are represented in the knowledge base.