• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.21-31
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• 2014

As the protein drug industry is growing, protein informations are indispensable for the protein drug development. NCBI and PDB in the U.S., the EMBL in Europe and the DDBJ in Japan are the representative centers for bio information and each center provides specific data for protein information. To obtain specific protein information, users are to be collect them from the service sites of each center and then combine or analyze for their purpose. To facilitate the accessibility to bio data, various R&D activities are running for development of diverse web services relevant to bio data in major data centers or small-scale projects. With the recognition of protein information as pivotal for the protein drug development, DrugBank in Canada, GDSC in the U.S. start to provide integrated informations between drugs and proteins. However, those service does not meet users' demands due to lack of diversity. In Korea, infra structures for bioinformatics are limited and the current services for protein drug information are providing only basic information of the drug including distribution data. This is a pilot study to construct a specialized service for protein drug information in Korean style breaking through the limitations of current services. This study proposed new fields for protein characterization information which had not been provided by current services and evaluated their effectiveness and usability by comparing them to the existing fields with expert survey. As a result, the newly proposed fields for protein characterization have been proven to be useful data fields for the service of protein drug information.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.57-67
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• 2024

This research investigates training methods for large language models to accurately identify sentiments and comprehend information about increasing and decreasing fluctuations in the financial domain. The main goal is to identify suitable datasets that enable these models to effectively understand expressions related to financial increases and decreases. For this purpose, we selected sentences from Wall Street Journal that included relevant financial terms and sentences generated by GPT-3.5-turbo-1106 for post-training. We assessed the impact of these datasets on language model performance using Financial PhraseBank, a benchmark dataset for financial sentiment analysis. Our findings demonstrate that post-training FinBERT, a model specialized in finance, outperformed the similarly post-trained BERT, a general domain model. Moreover, post-training with actual financial news proved to be more effective than using generated sentences, though in scenarios requiring higher generalization, models trained on generated sentences performed better. This suggests that aligning the model's domain with the domain of the area intended for improvement and choosing the right dataset are crucial for enhancing a language model's understanding and sentiment prediction accuracy. These results offer a methodology for optimizing language model performance in financial sentiment analysis tasks and suggest future research directions for more nuanced language understanding and sentiment analysis in finance. This research provides valuable insights not only for the financial sector but also for language model training across various domains.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1466-1477
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• 2016

Public key infrastructure(PKI), principle technology of the certificate, is a security technology providing functions such as identification, non-repudiation, and anti-forgery of electronic documents on the Internet. Our government and financial organizations use PKI authentication using ActiveX to prevent security accident on the Internet service. However, like ActiveX, plug-in technology is vulnerable to security and inconvenience since it is only serviceable to certain browser. Therefore, the research on HTML5 authentication system has been conducted actively. Recently, domestic bank introduced PKI authentication complying with web standard for the first time. However, it still has inconvenience to register a certification on each website because of same origin policy of web storage. This paper proposes the certificate based SSO protocol that complying with web standard to provide user authentication using certificate on several sites by going around same origin policy and its security proof.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1702-1721
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• 2019

A workflow process (or business process) management system helps to define, execute, monitor and manage workflow models deployed on a workflow-supported enterprise, and the system is compartmentalized into a modeling subsystem and an enacting subsystem, in general. The modeling subsystem's functionality is to discover and analyze workflow models via a theoretical modeling methodology like ICN, to graphically define them via a graphical representation notation like BPMN, and to systematically deploy those graphically defined models onto the enacting subsystem by transforming into their textual models represented by a standardized workflow process definition language like XPDL. Before deploying those defined workflow models, it is very important to inspect its syntactical correctness as well as its structural properness to minimize the loss of effectiveness and the depreciation of efficiency in managing the corresponding workflow models. In this paper, we are particularly interested in verifying very large-scale and massively parallel workflow models, and so we need a sophisticated analyzer to automatically analyze those specialized and complex styles of workflow models. One of the sophisticated analyzers devised in this paper is able to analyze not only the structural complexity but also the data-sequence complexity, especially. The structural complexity is based upon combinational usages of those control-structure constructs such as subprocesses, exclusive-OR, parallel-AND and iterative-LOOP primitives with preserving matched pairing and proper nesting properties, whereas the data-sequence complexity is based upon combinational usages of those relevant data repositories such as data definition sequences and data use sequences. Through the devised and implemented analyzer in this paper, we are able eventually to achieve the systematic verifications of the syntactical correctness as well as the effective validation of the structural properness on those complicate and large-scale styles of workflow models. As an experimental study, we apply the implemented analyzer to an exemplary large-scale and massively parallel workflow process model, the Large Bank Transaction Workflow Process Model, and show the structural complexity analysis results via a series of operational screens captured from the implemented analyzer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.223-228
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• 2023

According to the Korea Information Society Development Institute, OTT services grew at a rate of 33.4% in four yearsfrom 2017, when they were first launched.TheKorea Export-Import Bank announced in 2020 that the domestic OTT market was worth 780.1 billionKRW. This growth of the OTT market is expected to stimulate competition among OTT service platforms, and user satisfactionwithconvenience features, such as video recommendations, seems to be acting as an important factor in the competition.Currently, the OTT market uses a variety ofdata for customized recommendations, but the limitationis that it only uses datacollected within the app. Thereby we have proposed the use ofpersonal data collected outside the app for personalized recommendations, and the survey results showed that user satisfaction was 23.72% higher for recommended content based on the proposedmethod thanNetflix recommended content.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.300-305
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• 2023

This thesis is a study of content development utilizing media outlets to date through digital humans. The trend of global content is that the video content industry, including the character business, is growing. Lil Michela, who was selected as one of the 25 most influential people on the Internet by Time magazine in 2018, Nasua, who appeared in a SK Telecom commercial, and Rosie, who appeared in a Shinhan Bank commercial, are representative. Digital humans, which are driving new content, are computer-generated human characters with various characteristics and are referred to as virtual humans, metahumans, and cyber humans. With the rise of the metaverse after COVID-19, digital humans are being utilized in various forms such as media and marketing as an element of visual content. In the form of media, we can see that the boundaries between the offline and digital worlds are converging, and in the form of marketing, we can see that digital humans connect consumers and products more naturally. In the form of interaction, it is possible to achieve two-way communication through various methods of operation, and through these factors, it is possible to go beyond behavioral communication in the form of memorialization to emotional communication through AI technology. What can be seen through these processes is that through the currently developing digital human production methods and AI functions, not only experts but also non-experts can create quality contents, and new directions of contents will appear, and contents that can provide immediate feedback by bringing consumers and creators closer together have been studied.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.130-145
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• 2023

The digital transformation of finance is accelerating, and digital banking has already become a major banking channel. Banks have traditionally placed importance on CRM(Customer Relationship Management) and have tried to retain their loyal customers, who contribute significantly to the bank, such as long-term transactions, holding accounts with a certain balance or more, and holding loans. In this situation, this study exploratorily analyzed the consumer behavior of digital banking deposits in a major bank of Korea(1,145 samples). Statistical analysis was performed using SPSS. The main findings of the study are summarized as follows. It was found that there were differences of consumer behavior in digital banking deposits by generation, and the MZ generation used digital banking more on holidays than other generations. As a result of analyzing the behavior of existing loyal customers and regular customers of digital banking deposit, there was a significant difference in both the amount and period of the deposit. It was confirmed that the existing loyal customers of the bank also engage in consumer behavior that contributes to the bank in digital banking. In addition, the interaction between the customer type and the date of sign up for the deposit period, which is the goal setting of financial consumers, it was found that there was a significant effect. This study empirically analyzed the consumer behavior of digital banking in a situation where decrease of bank branches and encounters with digital banking. The major concepts of the consumer behavior theory are Loyal Customer, Goal Pursuit, and Habit, which were confirmed in an example of digital banking. The results of this study can suggest practical implications for existing banks and Internet-only banks, including the importance of customer management in digital banking.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.121-131
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• 2017

With emergence of Internet, social media, and mobile service, the consumers have actively presented their opinions and sentiment, and then it is spreading out real time as well. The user-generated text data on the Internet and social media is not only the communication text among the users but also the valuable resource to be analyzed for knowing the users' intent and sentiment. In special, economic participants have strongly asked that the social big data and its' analytics supports to recognize and forecast the economic trend in future. In this regard, the governments and the businesses are trying to apply the social big data into making the social and economic solutions. Therefore, this study aims to reveal the capability of social big data analysis for the economic use. The research proposed a social big data analysis model and an online consumer sentiment index. To test the model and index, the researchers developed an economic survey ontology, defined a sentiment dictionary for sentiment analysis, conducted classification and sentiment analysis, and calculated the online consumer sentiment index. In addition, the online consumer sentiment index was compared and validated with the composite consumer survey index of the Bank of Korea.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.44-51
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• 2013

Routers should perform fast IP address lookup for Internet to provide high-speed service. In this paper, we present a hybrid parallel IP address lookup structure composed of four-stage pipeline. It achieves parallelism at low cost by using multiple SRAMs in stage 2 and partitioned TCAMs in stage 3, and improves the performance through pipelining. The smart distributor in stage 1 does not transfer any IP address identical to previous one toward the next stage, but only uses the result of the previous lookup. So it improves throughput of lookup by caching effects, and decreases the access conflict to TCAM bank in stage 3 as well. In the last stage, the reorder buffer rearranges the completed IP addresses according to the input order. We evaluate the performance of our parallel pipelined IP lookup structure comparing with previous hybrid structure, using the real routing table and traffic distributions generated by Zipf's law.

• Journal of Information Management
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• v.27 no.1
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• pp.1-39
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• 1996

The purpose of this paper is to design a model of integrated OPAC called as EconRef. This model not only provides users of libraries with systematic, rapid information service, but also supports librarians to do their tasks effectively. The designed model is constructed based on two operating systems such as REGIS system and The Book House and is developed by using KPWin++ is an expert system shell which combines hypertext and expert system functions. The designed system consists of six modules ; three reference expert systems for document sources, experts and statistical sources; OPAC ; external database ; user's guide. For the evaluation of the designed system, performance of EconRef system is compared with that of the naive and expert reference librarians. And also the features of the system are compared with those of REGIS systems. The tests comparing BconRef system searching with librarians searching have shown that EconRef system is at least as good as searching with expert librarians and much superior to searching with naive librarians.