• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.125-155
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• 2010

Ontologies have been adopted in various business and scientific communities as a key component of the Semantic Web. Despite the increasing importance of ontologies, ontology developers still perceive construction tasks as a challenge. A clearly defined and well-structured methodology can reduce the time required to develop an ontology and increase the probability of success of a project. However, no reliable knowledge-engineering methodology for ontology development currently exists; every methodology has been tailored toward the development of a particular ontology. In this study, we developed a Graduation Screen Ontology (GSO). The graduation screen domain was chosen for the several reasons. First, the graduation screen process is a complicated task requiring a complex reasoning process. Second, GSO may be reused for other universities because the graduation screen process is similar for most universities. Finally, GSO can be built within a given period because the size of the selected domain is reasonable. No standard ontology development methodology exists; thus, one of the existing ontology development methodologies had to be chosen. The most important considerations for selecting the ontology development methodology of GSO included whether it can be applied to a new domain; whether it covers a broader set of development tasks; and whether it gives sufficient explanation of each development task. We evaluated various ontology development methodologies based on the evaluation framework proposed by G$\acute{o}$mez-P$\acute{e}$rez et al. We concluded that METHONTOLOGY was the most applicable to the building of GSO for this study. METHONTOLOGY was derived from the experience of developing Chemical Ontology at the Polytechnic University of Madrid by Fern$\acute{a}$ndez-L$\acute{o}$pez et al. and is regarded as the most mature ontology development methodology. METHONTOLOGY describes a very detailed approach for building an ontology under a centralized development environment at the conceptual level. This methodology consists of three broad processes, with each process containing specific sub-processes: management (scheduling, control, and quality assurance); development (specification, conceptualization, formalization, implementation, and maintenance); and support process (knowledge acquisition, evaluation, documentation, configuration management, and integration). An ontology development language and ontology development tool for GSO construction also had to be selected. We adopted OWL-DL as the ontology development language. OWL was selected because of its computational quality of consistency in checking and classification, which is crucial in developing coherent and useful ontological models for very complex domains. In addition, Protege-OWL was chosen for an ontology development tool because it is supported by METHONTOLOGY and is widely used because of its platform-independent characteristics. Based on the GSO development experience of the researchers, some issues relating to the METHONTOLOGY, OWL-DL, and Prot$\acute{e}$g$\acute{e}$-OWL were identified. We focused on presenting drawbacks of METHONTOLOGY and discussing how each weakness could be addressed. First, METHONTOLOGY insists that domain experts who do not have ontology construction experience can easily build ontologies. However, it is still difficult for these domain experts to develop a sophisticated ontology, especially if they have insufficient background knowledge related to the ontology. Second, METHONTOLOGY does not include a development stage called the "feasibility study." This pre-development stage helps developers ensure not only that a planned ontology is necessary and sufficiently valuable to begin an ontology building project, but also to determine whether the project will be successful. Third, METHONTOLOGY excludes an explanation on the use and integration of existing ontologies. If an additional stage for considering reuse is introduced, developers might share benefits of reuse. Fourth, METHONTOLOGY fails to address the importance of collaboration. This methodology needs to explain the allocation of specific tasks to different developer groups, and how to combine these tasks once specific given jobs are completed. Fifth, METHONTOLOGY fails to suggest the methods and techniques applied in the conceptualization stage sufficiently. Introducing methods of concept extraction from multiple informal sources or methods of identifying relations may enhance the quality of ontologies. Sixth, METHONTOLOGY does not provide an evaluation process to confirm whether WebODE perfectly transforms a conceptual ontology into a formal ontology. It also does not guarantee whether the outcomes of the conceptualization stage are completely reflected in the implementation stage. Seventh, METHONTOLOGY needs to add criteria for user evaluation of the actual use of the constructed ontology under user environments. Eighth, although METHONTOLOGY allows continual knowledge acquisition while working on the ontology development process, consistent updates can be difficult for developers. Ninth, METHONTOLOGY demands that developers complete various documents during the conceptualization stage; thus, it can be considered a heavy methodology. Adopting an agile methodology will result in reinforcing active communication among developers and reducing the burden of documentation completion. Finally, this study concludes with contributions and practical implications. No previous research has addressed issues related to METHONTOLOGY from empirical experiences; this study is an initial attempt. In addition, several lessons learned from the development experience are discussed. This study also affords some insights for ontology methodology researchers who want to design a more advanced ontology development methodology.

• Cross-Cultural Studies
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• v.50
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• pp.103-130
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• 2018

This research aims to explore the associated linguistic features and functions of Chinese as used for business trading purposes, and which is based on a discourse analysis through a case in which a Korean buyer and a Chinese supplier have exchanged Internet based e-mails. The research questions include first, the linguistic functions and characteristics of Chinese shown as identified in this trade case through e-mails, second, the use of Chinese trade specific terms, and third, the apparent and dynamic negotiation strategies that are identified as followed by the cultural value systems which are used for resolving interest conflicts and issues between the buyer and supplier in the course of negotiating business contracts between two parties. The participants of this research pertain to a Korean buyer, James and a Chinese supplier, Sonya. The associated data consists of 74 e-mails exchanged between the two parties, initiated in an effort to begin and complete a trade item, in this case namely the product of napkin holders. The research for the study is based on the discourse analysis and empirically analyses models of Chinese linguistic functions and features. The findings are the following. First, as identified, the specific Chinese functions used and sequenced in this trade case are of a procedure, request, informing, negotiation and persuasion. Second, the essential trade terms used in this business interaction involve the relevant issues of 1) ordering and price negotiating, 2) marking the origin of the products, 3) the arrangement of the product examination and customs declaration for the anticipated import items, 4) preparation of the necessary legal documents, and 5) the package and transport of the product in the final instance. Third, the impact of the similarities and differences in the cultural value systems between Korea and China on the negotiations and conflict resolution during a negotiated contract between two parties are speculated in terms of the use of culturally based techniques such as face-saving and the utilization of uncertainty-avoiding strategies as meant to prevent misunderstandings from developing between the parties. The concluding part of the study discusses the implications for a practical Chinese language education utilizing the linguistic functions and features of the Chinese culture and language strategies as useful in business associations for trading purposes, and the importance of intercultural communication styles based on similar of different identified cultural values as noted between two parties.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.65-76
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• 2023

In the field of technology entrepreneurship and startups, the development of Artificial Intelligence(AI) has emerged as a key topic for business model innovation. As a result, venture firms are making various efforts centered on AI to secure competitiveness(Kim & Geum, 2023). The purpose of this study is to analyze the relationship between the development of GenAI technology and the startup ecosystem by analyzing domestic news articles to identify trends in the technology startup field. Using BIG Kinds, this study examined the changes in GenAI-related news articles, major issues, and trends in Korean news articles from 1990 to August 10, 2023, focusing on the emergence of ChatGPT before and after, and visualized the relevance through network analysis and keyword visualization. The results of the study showed that the mention of GenAI gradually increased in the articles from 2017 to 2023. In particular, OpenAI's ChatGPT service based on GPT-3.5 was highlighted as a major issue, indicating the popularization of language model-based GenAI technologies such as OpenAI's DALL-E, Google's MusicLM, and VoyagerX's Vrew. This proves the usefulness of GenAI in various fields, and since the launch of ChatGPT, Korean companies have been actively developing Korean language models. Startups such as Ritten Technologies are also utilizing GenAI to expand their scope in the technology startup field. This study confirms the connection between GenAI technology and startup entrepreneurship activities, which suggests that it can support the construction of innovative business strategies, and is expected to continue to shape the development of GenAI technology and the growth of the startup ecosystem. Further research is needed to explore international trends, the utilization of various analysis methods, and the possibility of applying GenAI in the real world. These efforts are expected to contribute to the development of GenAI technology and the growth of the startup ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.53-68
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• 2024

Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4745-4749
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• 2012

The diagnosis of malignant mesothelioma (MM) remains a clinical challenge and the fluorescence in situ hybridization (FISH) assay has been reported to be one promising tool. The present meta-analysis aimed to establish the overall diagnostic accuracy of FISH for diagnosing MM. After a systematic review of English language studies, the sensitivity, specificity and other measures of accuracy of FISH in the diagnosis of MM were pooled using random-effects models. Summary receiver operating characteristic curves were applied to summarize overall test performance. Nine studies met our inclusion criteria, the pooled sensitivity and specificity for FISH for diagnosing MM being 0.72 (95% CI 0.67-0.76) and 1.00 (95% CI 0.98-1.00), respectively. The positive likelihood ratio was 34.5 (95% CI 14.5-82.10), the negative likelihood ratio was 0.24 (95% CI 0.16-0.36), and the diagnostic odds ratio was 204.9 (95% CI 76.8-546.6), the area under the curve being 0.99. Our data suggest that the FISH assay is likely to be a useful diagnostic tool for confirming MM. However, considering the limited studies and patients included, further large scale studies are needed to confirm these findings.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2445-2451
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• 2016

Background: To evaluate knowledge of Bangkok women regarding HPV and self-sampled HPV testing, and their attitudes towards testing. Materials and Methods: Thai women who had lived in Bangkok for more than 5 years, aged 25-to-65 years old, were invited to join the study. Participating women were asked to a complete self-questionnaire (Thai language), with literate assistance as needed. The questionnaire was divided into 3 parts: (I) demographic data, (II) knowledge and (III) attitudes towards self-sampled HPV testing. Before proceeding to Part III of the questionnaire, a 15-minute educational video of self-sampled HPV testing was presented to all participants. Results: Among 2,810 women who answered the questionnaires, 33.7% reported that they did not know about HPV. The characteristic features of these women were older age (> 50 years), lower income (< 600 USD/month), unemployed status, and non-attendees at cervical cancer screening. Only small numbers of women (4.6%) responded that they had heard about self-sampled HPV testing. After having information, 59.6% would not use the self-sampled HPV testing as a method of cervical cancer screening (non-acceptance). Factors significantly associated with the non-acceptance were older age, lower income, having no knowledge about HPV or self-collected HPV testing, a perception that the testing was unreliable and a concern that they might not be able to perform it correctly. Conclusions: Nearly half and almost all Bangkok women did not know about HPV and self-sampled HPV testing, respectively. Approximately 60% of Bangkok women refused to do the self-sampled HPV testing. Significant negative attitudes were concerns that the testing would be unreliable and a lack of confidence to perform the procedure correctly. Education about HPV and self-sampled HPV testing, ease of the procedure, or the testing models may increase rate of acceptability or positive attitudes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.1-17
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• 2007

As XML is becoming a de facto standard for distribution and sharing of information, the need for an efficient yet secure access of XML data has become very important. To enforce the fine-level granularity requirement, authorization models for regulating access to XML documents use XPath which is a standard for specifying parts of XML data and a suitable language for both query processing. An access control environment for XML documents and some techniques to deal with authorization priorities and conflict resolution issues are proposed. Despite this, relatively little work has been done to enforce access controls particularly for XML databases in the case of query access. Developing an efficient mechanism for XML databases to control query-based access is therefore the central theme of this paper. This work is a proposal for an efficient yet secure XML access control system. The basic idea utilized is that a user query interaction with only necessary access control rules is modified to an alternative form which is guaranteed to have no access violations using tree-aware metadata of XML schemes and set operators supported by XPath 2.0. The scheme can be applied to any XML database management system and has several advantages over other suggested schemes. These include implementation easiness, small execution time overhead, fine-grained controls, and safe and correct query modification. The experimental results clearly demonstrate the efficiency of the approach.

• Journal of Korean Society of Rural Planning
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• v.18 no.4
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• pp.13-26
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• 2012

The purpose of this study is to select the study area, which will be formed into Daegu Science Park as an national industrial complex, and to assess the landscape value based on biotop classification with different polygon forms, and to develop and computerize Biotop Value Assessment Tool (B-VAT) based on GIS. The result is as follows. First, according to the result of biotop classification based on an advanced analysis on preliminary data, a field study, and a literature review, total 13 biotop groups such as forrest biotop groups and total 63 biotop types were classified. Second, based on the advanced research on landscape value assessment model of biotop, we development biotop value assessment tool by using visual basic programming language on the ArcGIS. The first application result with B-VAT showed that the first grade was classified into 19 types including riverside forest(BE), the second grade 12 types including artificial plantation(ED), and the third class, the fourth grade, and the fifth grade 12 types, 2 types, and 18 types respectively. Also, according to the second evaluation result with above results, we divided a total number of 31 areas and 34 areas, which had special meaning for landscape conservation(1a, 1b) and which had meaning for landscape conservation(2a, 2b, 2c). As such, biotop type classification and an landscape value evaluation, both of which were suggested from the result of the study, will help to scientifically understand a landscape value for a target land before undertaking reckless development. And it will serve to provide important preliminary data aimed to overcome damaged landscape due to developed and to manage a landscape planning in the future. In particular, we expect that B-VAT based on GIS will help overcome the limitations of applicability for of current value evaluation models, which are based on complicated algorithms, and will be a great contribution to an increase in convenience and popularity. In addition, this will save time and improve the accuracy for hand-counting. However, this study limited to aesthetic-visual part in biotop assessment. Therefore, it is certain that in the future research comprehensive assessment should be conducted with conservation and recreation view.