• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.1032-1042
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• 2009

This research is for early extraction and utilization of semantic information from the tags in tagged Web image retrieval. Generally, users attach a tag to a Web image with little thought of the order, up to over 100 ones. In this paper, we suggest a method of selecting prior tags based on their importance when tagged images are uploaded, and using them in image retrieval. Ideas came from the recognition of the important tags which give a better description of the image as the tags sharing more semantic information with other tags of the same image. This method includes calculation of relation scores between tags based on WordNet and multilevel search of tagged images with the scores. For evaluation, we compared the suggested method and other retrieval methods searching images with simple matching of tags to a given keyword. As the results, we found the superiority of our method in precision and recall rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.1051-1066
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• 2000

According to the recent advances of digital encoding technologies and computing power, large amounts of multimedia informations such as image, graphic, audio and video are fully used in multimedia systems through Internet. By this, diverse retrieval mechanisms are required for users to search dedicated informations stored in multimedia systems, and especially it is preferred to use contents-based retrieval method rather than text-type keyword retrieval method. In this paper, we propose a new contents-based indexing and searching algorithm which aims to get both high efficiency and high retrieval performance. To achieve these objectives, firstly the proposed algorithm classifies images by a pre-processing process of edge extraction, range division, and multiple filtering, and secondly it searches the target images using spatial and textural characteristics of colors, which are extracted from the previous process, in a image. In addition, we describe the simulation results of search requests and retrieval outputs for several images of company's trade-mark using the proposed contents-based retrieval algorithm based on wavelet.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.29 no.3
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• pp.42-49
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• 2016

Objectives : The purpose of this study is to analyze research trends on tinea pedis in studies of Korean medicine.Methods : We searched papers using NDSL, KISS, RISS and KTKP(Korean Traditional Knowledge Portal). The first search used the keyword "Tinea pedis" in NDSL, KISS, RISS and KTKP. Used searching duration was not specified.Results : Studies found in NDSL, KISS and RISS were 122 and 118 studies were excluded. Studies found in KTKP were five papers and four studies of them were excluded. Finally five studies were selected and analyzed. Two studies of five selected ones were experimental researches and three studies were clinical researches. Among 2 researches of experimental researches, one of them was about antifungal efficacy of herbal medicines and ethahol extract of the mixture of Sophorae Subprostratae Radix, Aconiti Radix and Hibisci Syriaci Cortex and hot water extract of Phellodendri Cortex were effective. The other was about antifungal effect of the medicinal herb extraction method and vinegar extract was effective. Among 3 researches of clinical researches, there were one clinical study and two case studies. Functional soap containing herbal medicines and bee venom therapy were effective.Conclusions : As we looked for five researches, which were two experimental studies, one clinical study and two case studies. It is possible to treat tinea pedis with korean medical approach by conclusions of 5 researches. We expect that further researches will be proceeded and following results can be actively used as clinical treatments.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.62-69
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• 2009

The purpose of document summarization is to provide easy and quick understanding of documents by extracting summarized information from the documents produced by various application programs. In this paper, we propose a document summarization method that creates and analyzes a connection graph representing the similarity of keyword lists of sentences in a document taking into account the mean length(the number of keywords) of sentences of the document. We implemented a system that automatically generate a summary from a document using the proposed method. To evaluate the performance of the method, we used a set of 20 documents associated with their correct summaries and measured the precision, the recall and the F-measure. The experiment results show that the proposed method is more efficient compared with the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.39-50
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• 2017

Gamification in education widely used in the field of computer science (CS). The purpose of this study is to analyze the pre-studies of gamification cases in CS education and suggest the direction of CS education. For the study, an empirical research method was applied. Through keyword search, 1220 pre-studies were collected, among which 55 were compressed through the first and second extraction processes. In the results section, this study summarized the presented year, applied subject, subject of education, results and limitations. Additional study not only will analyze gamification of CS Education and compare with this study's results, but it will suggest the development direction of gamification in CS education in Korea.

• Fire Science and Engineering
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• v.28 no.2
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• pp.91-97
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• 2014

New types of fire accidents appear or the existing types disappeared because of rapidly changing society. We proposed a methodology of extracting new nouns from fire investigation data each of which is an accident report producted by fire investigators. The new nouns could be used in modifying the existing categories for classifying fire accidents. We analysed morphology of the product names and the ignition summaries using the proposed method for the fire accidents classified as the etc sub-category of the category of equipments involved in ignition. In this paper, we found "dryer" as a new sub-category of the agricultural equipment category and "boiler" in the seasonal appliance category from the product names of the fire accidents. We also extracted the new input keywords of "aquarium" and "monitor" in the commercial facilities category and the video, audio apparatus category from the ignition summaries respectively. Using the four subcategories, we reclassified 548 (14.39%) of 3,808 fire accidents assigned to the etc sub-category.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1832-1840
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• 1999

Since the existed Korean Web IR systems generally use boolean system, it is difficult to retrieve the information to be wanted at one time. Also, because of the feature that web documents have the frequent abbreviation and many links, the keyword extraction using the inverted document frequency extracts the improper keywords for adding ambiguous meaning problem. Therefore, users must repeat the modification of the queries until they get the proper information. In this paper, we design and implement the relevance feedback agent system for resolving the above problems. The relevance feedback agent system extracts the proper information in response to user's preferred keywords and stores these keywords in preference DB table. When users retrieve this information later, the relevance feedback agent system will search it adding relevant keywords to user's queries. As a result of this method, the system can reduce the number of modification of user's queries and improve the efficiency of the IR system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.255-263
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• 2015

In this paper, we suggest a plan to take advantage of the SNS data to proactively identify the information on crime risk factor and to prevent crime. Recently, SNS(Social Network Service) data have been used to build a proactive prevention system in a variety of fields. However, when users are collecting SNS data with simple keyword, the result is contain a large amount of unrelated data. It may possibly accuracy decreases and lead to confusion in the data analysis. So we present a method that can be efficiently extracted by improving the search accuracy through text mining analysis of SNS data.

• The Journal of Information Systems
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• v.30 no.1
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• pp.123-149
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• 2021

Purpose The purpose of this study is to define the anti-ESG activities of companies recognized by media by reflecting ESG recently attracted attention. This study extracts keywords for ESG controversies through association rule mining. Design/methodology/approach A research framework is designed to extract keywords for ESG controversies as follows: 1) From DeepSearch DB, we collect 23,837 articles on anti-ESG activities exposed to 130 media from 2013 to 2018 of 294 listed companies with ESG ratings 2) We set keywords related to environment, social, and governance, and delete or merge them with other keywords based on the support, confidence, and lift derived from association rule mining. 3) We illustrate the importance of keywords and the relevance between keywords through density, degree centrality, and closeness centrality on network analysis. Findings We identify a total of 26 keywords for ESG controversies. 'Gapjil' records the highest frequency, followed by 'corruption', 'bribery', and 'collusion'. Out of the 26 keywords, 16 are related to governance, 8 to social, and 2 to environment. The keywords ranked high are mostly related to the responsibility of shareholders within corporate governance. ESG controversies associated with social issues are often related to unfair trade. As a result of confidence analysis, the keywords related to social and governance are clustered and the probability of mutual occurrence between keywords is high within each group. In particular, in the case of "owner's arrest", it is caused by "bribery" and "misappropriation" with an 80% confidence level. The result of network analysis shows that 'corruption' is located in the center, which is the most likely to occur alone, and is highly related to 'breach of duty', 'embezzlement', and 'bribery'.