• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.57-66
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• 2022

In this paper, we propose a legal document search method that uses the Sentence-BERT model. The general public who wants to use the legal search service has difficulty searching for relevant precedents due to a lack of understanding of legal terms and structures. In addition, the existing keyword and text mining-based legal search methods have their limits in yielding quality search results for two reasons: they lack information on the context of the judgment, and they fail to discern homonyms and polysemies. As a result, the accuracy of the legal document search results is often unsatisfactory or skeptical. To this end, This paper aims to improve the efficacy of the general public's legal search in the Supreme Court precedent and Legal Aid Counseling case database. The Sentence-BERT model embeds contextual information on precedents and counseling data, which better preserves the integrity of relevant meaning in phrases or sentences. Our initial research has shown that the Sentence-BERT search method yields higher accuracy than the Doc2Vec or TF-IDF search methods.

• The Journal of Korean Obstetrics and Gynecology
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• v.36 no.3
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• pp.25-45
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• 2023

Objectives: The purpose of this study is to review the clinical research trends of ovarian cysts and to recognize the efficacy of Korean medicine intervention. Methods: Based on four domestic databases, including Korean studies Information Service System (KISS), Oriental Medicine Advanced Searching Integrated System (OASIS), Korean Medical Database (KMbase) and Research Information Sharing Service (RISS), we analyzed the case reports using Korean medicine intervention, which include acupuncture, moxibustion and herbal medicine. Data retrieval was carried out from May 12^th, to 18^th, 2022, and a total of 9 papers were included. Results: All papers were published in Korea and they contain seventeen case reports in total. The most frequently used intervention was herbal medicine, especially Gyejibokryeong-hwan-gami (桂枝茯苓丸加味), Guichulpajing-tang-gagam (歸朮破癥湯加減), Guibiondam-tang-gami (歸脾溫膽湯加味). Most cases reported statistically significant results on using Korean-medicine intervention. Also, there was no serious side effect of Korean medicine. Conclusions: In this study, we investigated the efficacy of Korean medicine intervention as an adjuvant therapy for ovarian cyst patients and research trends on ovarian cysts. Further studies are needed to supplement the safety and the evaluation of Korean medicine. However, the results should be taken cautiously as more clinical studies are needed.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.29-36
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• 2009

Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, is an important data mining problem with broad applications. Since a sequential pattern in DNA sequences can be a motif, we studied to find sequential patterns in DNA sequences. Most previously proposed mining algorithms follow the exact matching with a sequential pattern definition. They are not able to work in noisy environments and inaccurate data in practice. Theses problems occurs frequently in DNA sequences which is a biological data. We investigated approximate matching method to deal with those cases. Our idea is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call approximated pattern. The existing PrefixSpan algorithm can successfully find sequential patterns in a long sequence. We improved the PrefixSpan algorithm to find approximate sequential patterns. The experimental results showed that the number of repeats from the proposed method was 5 times more than that of PrefixSpan when the pattern length is 4.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.4
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• pp.67-84
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• 2009

Cyber Textbook Museum is created by the Korean Educational Development Institute in part of the project to manage the knowledge and information of Korea to promote understanding of Korean education and its history. The original and full text of textbooks dating from the 1890s to the present have been digitized and arranged for easy access over internet. An exclusive portal site dealing with Korean textbooks and curriculum materials was made to provide not only the directory service of textbooks and curriculums in diverse data classifications, school levels, years/periods and subjects but also the keyword search by searching engine. Users can search the necessary materials easily and systematically over the screen and use all the functions except save, capture and print. The management system for textbook image(DjVu format), search system and DRM(Digital Rights Management) system were developed. Finally, four suggestions are proposed which are related in the aspects of policy, technical, systematic aspects for active and tremendous use of the site.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.104-110
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• 2023

In the user-centered design paradigm, information systems are created entirely tailored to the users who will use them. When the functions of a complex system meet a simple user interface, users can use the system conveniently. While web personalization services are emerging as a major trend in portal services, portal companies are competing for a second service, such as introducing 'integrated communication platforms'. Until now, the role of the portal has been content and search, but this time, the goal is to create and provide the personalized services that users want through a single platform. Personalization service is a login-based cloud computing service. It has the characteristic of being able to enjoy the same experience at any time in any space with internet access. Personalized web services like this have the advantage of attracting highly loyal users, making them a new service trend that portal companies are paying attention to. Researchers spend a lot of time collecting research-related information by accessing multiple information sources. There is a need to automatically build interest information profiles for each researcher based on personal presentation materials (papers, research projects, patents). There is a need to provide an advanced customized information service that regularly provides the latest information matched with various information sources. Continuous modification and supplementation of each researcher's information profile of interest is the most important factor in increasing suitability when searching for information. As researchers' interest in unstructured information such as technology markets and research trends is gradually increasing from standardized academic information such as patents, it is necessary to expand information sources such as cutting-edge technology markets and research trends. Through this, it is possible to shorten the time required to search and obtain the latest information for research purposes. The interest information profile for each researcher that has already been established can be used in the future to determine the degree of relationship between researchers and to build a database. If this customized information service continues to be provided, it will be useful for research activities.

• Korean Journal of Radiology
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• v.22 no.1
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• pp.63-71
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• 2021

Objective: To identify the CT findings associated with treatment failure after antibiotic therapy for acute appendicitis. Materials and Methods: Altogether, 198 patients who received antibiotic therapy for appendicitis were identified by searching the hospital's surgery database. Selection criteria for antibiotic therapy were uncomplicated appendicitis with an appendiceal diameter equal to or less than 11 mm. The 86 patients included in the study were divided into a treatment success group and a treatment failure group. Treatment failure was defined as a resistance to antibiotic therapy or recurrent appendicitis during a 1-year follow-up period. Two radiologists independently evaluated the following CT findings: appendix-location, involved extent, maximal diameter, thickness, wall enhancement, focal wall defect, periappendiceal fat infiltration, and so on. For the quantitative analysis, two readers independently measured the CT values at the least attenuated wall of the appendix by drawing a round region of interest on the enhanced CT (HU_post) and non-enhanced CT (HU_pre). The degree of appendiceal wall enhancement (HU_sub) was calculated as the subtracted value between HU_post and HU_pre. A logistic regression analysis was used to identify the CT findings associated with treatment failure. Results: Sixty-four of 86 (74.4%) patients were successfully treated with antibiotic therapy, with treatment failure occurring in the remaining 22 (25.5%). The treatment failure group showed a higher frequency of hypoenhancement of the appendiceal wall than the success group (31.8% vs. 7.8%; p = 0.005). Upon quantitative analysis, both HU_post (46.7 ± 21.3 HU vs. 58.9 ± 22.0 HU; p = 0.027) and HU_sub (26.9 ± 17.3 HU vs. 35.4 ± 16.6 HU; p = 0.042) values were significantly lower in the treatment failure group than in the success group. Conclusion: Hypoenhancement of the appendiceal wall was significantly associated with treatment failure after antibiotic therapy for acute appendicitis.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.151-158
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• 2006

In this paper, we proposed a new audio fingerprint extraction method, based on Philips' music retrieval algorithm, which uses the energy difference of neighboring filter-bank and probabilistic characteristics of music. Since Philips method uses too many filter-banks in limited frequency band, it may cause audio fingerprints to be highly sensitive to additive noises and to have too high correlation between neighboring bands. The proposed method improves robustness to noises by reducing the number of filter-banks while it maintains the discriminative power by representing the energy difference of bands with 2 bits where the quantization levels are determined by probabilistic characteristics. The correlation which exists among 4 different levels in 2 bits is not only utilized in similarity measurement. but also in efficient reduction of searching area. Experiments show that the proposed method is not only more robust to various environmental noises (street, department, car, office, and restaurant), but also takes less time for database search than Philips in the case where music is highly degraded.

• The Journal of Internal Korean Medicine
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• v.45 no.4
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• pp.549-567
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• 2024

Objectives: This study was aimed at evaluating the effectiveness and safety of Danggui buxue decoction (DBD) for iron deficiency anemia (IDA) by systematic review and meta-analysis of the randomized controlled trials (RCTs). Methods: Randomized controlled trials on the treatment of DBD for IDA patients were selected from among the literature published from the beginning of each database to May 30, 2023 in nine domestic and foreign databases (PubMed, EMBASE, Cochrane, Chinese Academic Journals (CAJ), CiNii Research, J-STAGE, Oriental Medicine Advanced Searching Integrated System (OASIS), Research Information Sharing Service (RISS), and ScienceON). The quality of the literature was evaluated using the Cochrane ROB tool 2.0 (ROB2) and GRADE method. The meta-analysis was conducted using RevMan5.4. Results: A total of 636 patients with IDA were finally selected from the 7 RCTs. The meta-analysis showed that the treatment groups that underwent both DBD and conventional treatment were statistically higher than the control groups that performed only conventional treatment in all indicators that showed effectiveness of DBD such as red blood cell (mean difference (MD) 0.38×10¹²/L, 95% CI: 0.16-0.60), hemoglobin (MD 12.45 g/L, 95% CI: 10.27-14.63), serum ferritin (MD 3.50 ㎍/L, 95% CI: 1.71-5.29), and total effective rate (relative risk (RR) 1.13, 95% CI: 1.05-1.21). The incidence of adverse events was 0.39 times lower in the DBD group than in the conventional group (RR 0.39, 95% CI: 0.22-0.70). Conclusion: This study demonstrated the effectiveness and safety of DBD with conventional treatment and further provided a basis for administering DBD to patients with IDA in clinical treatment.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.