• Journal of Ecology and Environment
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• v.48 no.3
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• pp.263-276
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• 2024

Background: Repeated and severe fires have led to a large investment in research directed towards recapturing the natural values of Indonesia's peatland forest resources. The aim of this study was to identify the patterns and trends in research on peatland restoration-related literature available on the Scopus database. Methods in this paper a bibliometric methodology, the Scopus database and VOSviewer were used explore the trends in the published peatland restoration literature in the period 1994-2021; the leading journals and most influential authors, affiliations, countries, documents and research themes were identified. Results: Three hundred and seventeen documents including 266 journal articles were identified. The leading journals based on numbers of articles published and citations were Restoration Ecology and Ecological Engineering. Authors affiliated to institutions in Canada and the United Kingdom were the most influential. Indonesia was the third most influential based on numbers of documents. The most influential article was "The underappreciated potential of peatlands in global climate change mitigation strategies" by Liefield J in Nature Communications with an annual average citation rate of 66/year. A keyword co-occurrence network identified nine main themes in peat restoration research. Conclusions: The findings of the study are used to outline the types of research in peat restoration now required to meet the outstanding and unmet challenges confronted in Indonesia. Three significant challenges have been identified: (1) anthropogenic, those that encompass issues related to community acceptance and participation in peatland restoration, (2) ecological, those associated with severely degraded peatlands, and (3) economic, the absence of secure funding to cover substantial costs.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.129-143
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• 2012

Recently, the rapid progress of a number of standardized web technologies and the proliferation of web users in the world bring an explosive increase of producing and consuming information documents on the web. In addition, most companies have produced, shared, and managed a huge number of information documents that are needed to perform their businesses. They also have discretionally raked, stored and managed a number of web documents published on the web for their business. Along with this increase of information documents that should be managed in the companies, the need of a solution to locate information documents more accurately among a huge number of information sources have increased. In order to satisfy the need of accurate search, the market size of search engine solution market is becoming increasingly expended. The most important functionality among much functionality provided by search engine is to locate accurate information documents from a huge information sources. The major metric to evaluate the accuracy of search engine is relevance that consists of two measures, precision and recall. Precision is thought of as a measure of exactness, that is, what percentage of information considered as true answer are actually such, whereas recall is a measure of completeness, that is, what percentage of true answer are retrieved as such. These two measures can be used differently according to the applied domain. If we need to exhaustively search information such as patent documents and research papers, it is better to increase the recall. On the other hand, when the amount of information is small scale, it is better to increase precision. Most of existing web search engines typically uses a keyword search method that returns web documents including keywords which correspond to search words entered by a user. This method has a virtue of locating all web documents quickly, even though many search words are inputted. However, this method has a fundamental imitation of not considering search intention of a user, thereby retrieving irrelevant results as well as relevant ones. Thus, it takes additional time and effort to set relevant ones out from all results returned by a search engine. That is, keyword search method can increase recall, while it is difficult to locate web documents which a user actually want to find because it does not provide a means of understanding the intention of a user and reflecting it to a progress of searching information. Thus, this research suggests a new method of combining ontology-based search solution with core search functionalities provided by existing search engine solutions. The method enables a search engine to provide optimal search results by inferenceing the search intention of a user. To that end, we build an ontology which contains concepts and relationships among them in a specific domain. The ontology is used to inference synonyms of a set of search keywords inputted by a user, thereby making the search intention of the user reflected into the progress of searching information more actively compared to existing search engines. Based on the proposed method we implement a prototype search system and test the system in the patent domain where we experiment on searching relevant documents associated with a patent. The experiment shows that our system increases the both recall and precision in accuracy and augments the search productivity by using improved user interface that enables a user to interact with our search system effectively. In the future research, we will study a means of validating the better performance of our prototype system by comparing other search engine solution and will extend the applied domain into other domains for searching information such as portal.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Management & Information Systems Review
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• v.33 no.2
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• pp.101-118
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• 2014

In the mid-2000s, Web 2.0 appears and is becoming a general cultural code with the keyword of participation, sharing, and openness. Web 2.0, in which consumption is being transformed by the participatory web culture, has evolved. However, associated with the evolution of Web 2.0, several significant concerns appears in a society. Among them, this study will focuses on the cyber-ethics issues. There are limitations to solve the cyber-ethics problems only in the technical and legal approaches. Therefore, the current article intends to consider comprehensively the antecedents of cyber-ethics such as individual characteristics, social influence, and cultural characteristics. Specifically, (1) Do individual characteristics(i.e., self-efficacy, locus of control) affect cyber-ethics in the Web 2.0 environment?, (2) Do social influence(i.e., subjective norm) have an effect on cyber-ethics?, (3) Do cyber -ethics have an impact on user participation in the Web 2.0 services(i.e., retrieval and creation)?, finally (4) Do international cultural difference have a moderation effect on the relationship between cyber-ethics and user participation? For testing empirically the hypothesized research model, this study collected questionnaires in South Korea as well as U.S.A. The results showed that individual characteristics and social influence affect cyber-ethics toward user's creative activities in Web 2.0 sites.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.145-151
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• 2020

'Hansik', or Korean cuisine is one of Korea national brands. To understand the domestic consumer awareness of Korean cuisine, data was gathered under the keyword search, 'Hansik.' Textom 3.5 was used to gather data from blogs, news media found on Naver from November 1, 2018, to October 31, 2019. The results from frequency and TF-IDF analysis indicate that the 'buffet' had the largest proportion in terms of consumer awareness to Hansik. Also, broadcasting contents starring star chefs had a great influence. The Hansik awareness did not remain in the domains of its traditionality, but also branched into extents into areas such as fusional and gourmet cuisine. UCINET6 and NetDraw were used to conduct CONCOR analysis. Four cluster formations have been found; various food cultural cluster, high-end restaurant cluster referring to aired restaurants on media, Hansik brand cluster, and Hansik buffet cluster. This study proposes presenting a various menu of Hansik which use a multiple number of ingredients. Also, a promotion that introduces fine Hansik and a development of marketing views and media contents about the convenient HMRs make the associated imagery of Hansik to be strengthen.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

• Korean Journal of Acupuncture
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• v.30 no.3
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• pp.145-150
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• 2013

Objectives : The aim of this study is to review the acupoints used in cocaine studies and interpret the effectiveness in an aspect of meridian theory of Korean medicine. Methods : Authors searched 50 articles in PubMed, 16 in KISS, 9 in OASIS, 40 in NDSL, and 19 in DBPIA, with the keyword of 'cocaine' or 'acupuncture'. The articles written in English only were included. The articles related with cocaine(abuse, dependence, sensitization, intake, withdrawal sign, withdrawal syndrome, reinstatement, seeking) only were subjected. The articles which used manual- or electro-acupuncture were included, and auricular was excluded. Results : The most frequently used acupoint was HT7, while LI4, LU9, ST36, and SP6 were used once respectively. HT7 could be understood to be used from the meaning of the name as well as the theory that Heart Meridian is deeply related with the brain function. LU9 seems to be used to enhance the effect of HT7. LI4 is thought to control reverting yin that flows toward the top of head following the theory of Jang Bu Sang Tong. ST36 appears to be used because it could regulate stress reaction that reverting yin is associated with. SP6 seems to have effect on brain function due to its ability to control spiritual disorder. Conclusions : The acupoints used in the cocaine studies are thought to influence the brain function through diverse mechanism, and Jang Bu Sang Tong theory seems to be involved in the mechanism, at least in part.

• Journal of Korean Ophthalmic Optics Society
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• v.20 no.4
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• pp.415-423
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• 2015

Purpose: We conducted a study on the brand name types of optical shop in the region of Daegu to exploit the data necessary for a new brand naming. Methods: The characteristics of the names including the concept and function, phrasing compositions - whether the names are Korean words, English words or combination of the two, or others, and whether the names are descriptive, allusive or coined, alternative names, and most frequently used names were studied and analyzed. Results: For those in Korean words, the most frequently appeared consonant was 'ㅇ' then 'ㅅ'. In combination words, either in Korean and English combination or others, 57.1% of the names were in Korean, or 32.7% of the names were in English. As for number of syllables, 3 syllables consumed 30.4% and 2 and 4 syllables were in similar proportions of 29.7% and 25.0%, respectively. The proportions of allusive and descriptive names were 17.0% and 13.3%, respectively. As for alternative creation type, the type with combination of words came first, and then use of symbols came second. For other types, there were high number of brand names that contained the names of other business types and names of the districts in which the stores were located. Lastly, the most frequently used keyword was 'eye', which was used 45 times, and then came 'dang' and 'angyeong'. Conclusions: When starting a business and making an appropriate brand name, it must be easy to say and remember as well as meaningful. As such, a brand name for an optical shop should not only be creative, but also be associated with the business and emanate favorable impression.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.