• Informatization Policy
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• v.23 no.3
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• pp.26-42
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• 2016

Recently, with the rapid growth of the O2O market, Fintech combining the finance and ICT technology is drawing attention as innovation to lead "O2O of finance", along with Fintech-based payment, authentication, security technology and related services. For new technology industries such as Fintech, technical sources, related systems and regulations are important but previous studies on Fintech lack in-depth research about systems and technological trends of the domestic Fintech industry. Therefore, this study aims to analyze domestic Fintech trends and find the insights for the direction of technology and systems of the future domestic Fintech industry by comparing Kakao Pay and Samsung Pay, the two domestic representative mobile payment services. By conducting a complete enumeration survey about the tweets mentioning Fintech until June 2016, this study visualized topics extraction, sensitivity analysis and keyword analyses. According to the analysis results, it was found that various topics have been created in the technologies and systems between 2014 and 2016 and different keywords and reactions were extracted between topics of Samsung Pay based on "devices" such as Galaxy and Kakao Pay based on "service" such as KakaoTalk. This study contributes to analyzing the unstructured data of social media by period by using social media mining and quantifying the expectations and reactions of consumers to services through the sentiment analysis. It is expected to be the foundation of Fintech industry development by presenting a strategic direction to Fintech related practitioners.

• Journal of Korean Society of Disaster and Security
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• v.12 no.4
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• pp.15-26
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• 2019

Anjunshinmungo (The safety e-report) has been in operation since 2014, and there are about 1 million cumulative reports by June 2019. This study analyzes the contents of more than 1 million safety newspapers reported at the present time of information age to determine how powerful and meaningful the people's voice and interest are. In particular, we are interested in forecasting ability. We wanted to check whether the report of the safety newspaper was related to possible disasters. To this end, the researchers received data reported in the safety newspaper as text and analyzed it by natural language analysis methodology. Based on this, the newspaper articles during the analysis of the safety newspaper were analyzed, and the correlation between the contents of the newspaper and the newspaper was analyzed. As a result, accidents occurred within a few months as the number of reports related to response and confirmation increased, and analyzing the contents of safety reports previously reported on social instability can be used to predict future disasters.

• Journal of KIISE
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• v.42 no.12
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• pp.1522-1534
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• 2015

This work presents a new method that can predict, without the use of training data, whether an input essay is written on a given topic. ConceptNet is a common-sense knowledge base that is generated automatically from sentences that are extracted from a variety of document types. An essay prompt is the topic that an essay should be written about. The method that is proposed in this paper uses ConceptNet and an essay prompt to decide whether or not an input essay is off-topic. We introduce a way to find the shortest path between two nodes on ConceptNet, as well as a way to calculate the semantic similarity between two nodes. Not only an essay prompt but also a student's essay can be represented by concept nodes in ConceptNet. The semantic similarity between the concepts that represent an essay prompt and the other concepts that represent a student's essay can be used for a calculation to rank "on-topicness" ; if a low ranking is derived, an essay is regarded as off-topic. We used eight different essay prompts and a student-essay collection for the performance evaluation, whereby our proposed method shows a performance that is better than those of the previous studies. As ConceptNet enables the conduction of a simple text inference, our new method looks very promising with respect to the design of an essay prompt for which a simple inference is required.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.385-389
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• 2020

The medical drama has developed into a story centered on 'people', raising viewers' sympathy. The story of the drama is the true life story of doctors, patients and families. It is also a story that reminds me of 'a little special day of our ordinary people'. And the song played and sung by five characters in the drama became a factor that stimulates nostalgia and increases immersion. The highest viewer rating was 14.1%, and 51,584 blogs alone were registered. According to the big data analysis, the related words were 'Wise OST', 'Album Name', 'Artist Name', 'Two Hours in a row', 'Record', 'Remake', 'OST Revealed', 'Advertisement Revenue', 'Playlist', 'Aroha' and 'Cho Jung-seok'. The commercialization of medical dramas includes 'Sales of Drama OST Albums', 'Organizing Online Live Concerts (PPL in Advertising)', 'Publishing Piano Music', 'Picture of People-Oriented Photography', 'Making Music Video Editing Drama Highlight', 'YouTube Upload Profits', 'Mask' and 'Disinfectant'. it is predicted that the touching story of Corona 19 and the charming humanity will unfold. The limitations of the research will require analysis of various works by genre and attempts to analyze consumer values by industry.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.2
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• pp.67-83
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• 2020

Many local governments in Korea provide online services for people to easily access the audio-visual archives of events occurring in the area. However, the current method of managing these archives of the local governments has several problems in terms of compatibility with other organizations and convenience for searching of the archives because of the lack of standard metadata and the low utilization of image information. To solve these problems, we propose the metadata design and machine learning-based automatic indexing technology for the efficient management of the image archives of local governments in Korea. Moreover, we design metadata items specialized for the image archives of local governments to improve the compatibility and include the elements that can represent the basic information and characteristics of images into the metadata items, enabling efficient management. In addition, the text and objects in images, which include pieces of information that reflect events and categories, are automatically indexed based on the machine learning technology, enhancing users' search convenience. Lastly, we developed the program that automatically extracts text and objects from image archives using the proposed method, and stores the extracted contents and basic information in the metadata items we designed.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.121-129
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• 2015

With the explosive growth of information about books, there is a growing number of customers who find it difficult to pick a book. Against the backdrop, the importance of a book recommendation system becomes greater, through which appropriate information about books could be offered then to encourage customers to buy a book in the end. However, existing recommendation systems based on the bibliographical information or user data reveal the reliability issue found in their recommendation results. This is why it is necessary to reflect semantic information extracted from the texts of a book's main body in a recommendation system. Accordingly, this paper suggests a method for extracting keywords from the main body of novels, as a preceding research, by using TF-IDF method as well as the text structure. To this end, the texts of 100 novels have been collected then to divide them into four structural elements of preface, dialogue, non-dialogue and closing. Then, the TF-IDF weight of each keyword has been calculated. The calculation results show that the extraction accuracy of keywords improves by 42.1% in performance when more weight is given to dialogue while including preface and closing instead of using just the main body.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.377-386
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• 2003

In this paper, we present an application layer protocol to support secure wireless Internet services, called Application Layer Security(ALS). The drawbacks of the two traditional approaches to secure wireless applications motivated the development of ALS. One is that in the conventional application-specific security protocol such as Secure HyperText Transfer Protocol(S-HTTP), security mechanism is included in the application itself. This gives a disadvantage that the security services are available only to that particular application. The other is that a separate protocol layer is inserted between the application and transport layers, as in the Secure Sockets Layer(SSL)/Transport Layer Security(TLS). In this case, all channel data are encrypted regardless of the specific application's requirements, resulting in much waste of network resources. To overcome these problems, ALS is proposed to be implemented on top of HTTP so that it is independent of the various transport layer protocols, and provides a common security interface with security applications so that it greatly improves the portability of security applications. In addition, since ALS takes advantages of well-known TLS mechanism, it eliminates the danger of malicious attack and provides applications with various security services such as authentication, confidentiality integrity and digital signature, and partial encryption. We conclude this paper with an example of applying ALS to the solution of end-to-end security in a present commercial wireless protocol stack, Wireless Application Protocol.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.67-72
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• 2003

In this paper, we study the enhancement of VQ (Vector Quantization) design for text dependent speaker recognition. In a concrete way, we present the non-Iterative method which makes a vector quantization codebook and this method Is nut Iterative learning so that the computational complexity is epochally reduced. The proposed semi-noniterative VQ design method contrasts with the existing design method which uses the iterative learning algorithm for every training speaker. The characteristics of a semi-noniterative VQ design is as follows. First, the proposed method performs the iterative learning only for the reference speaker, but the existing method performs the iterative learning for every speaker. Second, the quantization region of the non-reference speaker is equivalent for a quantization region of the reference speaker. And the quantization point of the non-reference speaker is the optimal point for the statistical distribution of the non-reference speaker In the numerical experiment, we use the 12th met-cepstrum feature vectors of 20 speakers and compare it with the existing method, changing the codebook size from 2 to 32. The recognition rate of the proposed method is 100% for suitable codebook size and adequate training data. It is equal to the recognition rate of the existing method. Therefore the proposed semi-noniterative VQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.457-488
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• 2015

In this study, we analyzed the current research state of Library and Information science in top 20 journals from 1990 to 2015, in subject and method perspectives. We developed weighted subject-method network to investigate on centralities of a subject and a method as well as their relations. This network is composed of subject nodes and method nodes and gives a weight on each node by topic occurrence. As a result, for 25 years, management information system, information need analysis, bibliometrics, information policy were top topics. Modeling, literature review, scientific research impact analysis, web data analysis were top methods. A recent rise of text mining is highlighted. We also analyzed communities made from the past 25 years and the recent 5 years. Bibliometrics is extending its field by applying various network analyzing algorithms. Text mining is specialized in medical information system and user interface. This result identifies the interests of excellent studies in Library and Information Science. It also can be fundamental resource for the development of Library and Information Science.

• Journal of the Korea Society for Simulation
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• v.25 no.3
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• pp.107-116
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• 2016

The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.