• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.373-386
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• 2013

In this research, we specify the image consumers' preferred image quality ranges based on objective image quality evaluation factors and follow a method which measures preference of the natural image scenes. In other words, according to No-Reference, we select dynamic range, color, and contrast as factors of image quality measurements. For collecting sample images, we choose the preferred 200 landscapes which have over 30 recommendations by image consumers on the internet photo gallery. According to the scores of three objective factors of image quality measurements, the final expected score which means the image quality preference is measured and its total score is 100 points. In the main test, the actual image sample shows dynamic range 10 stop, LAB mean value L:54.7, A:2.96, B:-15.84, and RSC contrast 376.9. Total 200 image samples' normal distribution z value represents in dynamic range 0.21, LAB mean value L:0.15, A:0.38, B:0.13, and RSC contrast 0.08. In the standard normal distribution table, we can convert the z value as a percentage; dynamic range is 8.32%, LAB mean value is L:5.96%, A:14.8%, B:5.17%, and RSC contrast is 3.19%. And then, we convert the percentage values into the scores of 100; dynamic range is 91.68, LAB mean value is 91.36, and RSC contrast is 96.81. Therefore, we can conclude that the sample image's total mean score is 94.99 based on three objective image quality factors. Throughout our proposed image quality assessment model, we can measure the preference value of natural scenes. Also, we can specify the preferred image quality representation ranges and measure the expected image quality preference.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Korean journal of communication and information
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• v.34
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• pp.196-243
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• 2006

The popularity of Korea pop culture, which called as the name of "Korea wave", has started to spread out in China and other Asian states from late-1990's. The study about "Korea wave" until now, however, have prevailed within an economic point of view. So, I would like to clarify that this dissertation raises a question in exiting argument and explains the identity of "Korea wave" by investigating the details of pop culture contents of Korea, and understanding of chinese receiver. It shows that chinese receiver, watching the movie , has estimated in the affirmative viewpoint after I have analyzed a reply of movie web-site in China. The main features of this analysis prove that there are a lot of good estimation when chinese receiver have seen that movie because it has been well-matched with emotion and fun of story and attraction in the movie. In that order, Some Chinese netizen evaluated that there are some negative point of view as the main actress has a strange and crazy behavior. I have also found that Korea pop culture contents has not given to them good image and chinese receiver had a tendency to view objectively to classify with strength and weakness. Analysis to contrast understanding of Chinese netizen with Korea netizen showed that Korea netizen emphasized fun of story, however, Chinese netizen showed that they had a lot of opinion to be fresh and realistic relatively. In conclusion, I would like herewith to identify that there are some differences between Chinese netizen and Korean netizen after contacting the movie. The reason has showed that understanding about the same object can be a great deal of various consideration in two more diverse cultures which have many different social-cultural and historical situation.

• Progress in Medical Physics
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• v.26 no.3
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• pp.119-126
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• 2015

The purpose of this study is to analyze motion-induced dose error generated by each tumor motion parameters of irregular tumor motion in helical tomotherapy. To understand the effect of the irregular tumor motion, a simple analytical model was simulated. Moving cases that has tumor motion were divided into a slightly irregular tumor motion case, a large irregular tumor motion case and a patient case. The slightly irregular tumor motion case was simulated with a variability of 10% in the tumor motion parameters of amplitude (amplitude case), period (period case), and baseline (baseline case), while the large irregular tumor motion case was simulated with a variability of 40%. In the phase case, the initial phase of the tumor motion was divided into end inhale, mid exhale, end exhale, and mid inhale; the simulated dose profiles for each case were compared. The patient case was also investigated to verify the motion-induced dose error in 'clinical-like' conditions. According to the simulation process, the dose profile was calculated. The moving case was compared with the static case that has no tumor motion. In the amplitude, period, baseline cases, the results show that the motion-induced dose error in the large irregular tumor motion case was larger than that in the slightly irregular tumor motion case or regular tumor motion case. Because the offset effect was inversely proportion to irregularity of tumor motion, offset effect was smaller in the large irregular tumor motion case than the slightly irregular tumor motion case or regular tumor motion case. In the phase case, the larger dose discrepancy was observed in the irregular tumor motion case than regular tumor motion case. A larger motion-induced dose error was also observed in the patient case than in the regular tumor motion case. This study analyzed motion-induced dose error as a function of each tumor motion parameters of irregular tumor motion during helical tomotherapy. The analysis showed that variability control of irregular tumor motion is important. We believe that the variability of irregular tumor motion can be reduced by using abdominal compression and respiratory training.

• The Journal of Natural Sciences
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• v.10 no.1
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• pp.209-216
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• 1998

The results of the study of diving the 21st century's Korea fashion market into consumer market, fashion market, and a new marketing strategy are as follows. The 21st consumer market is First, a fashion democracy phenomenon. As many people try to leave unconditional fashion following, consumer show a phenomenon to choose and create their own fashion by subjective judgements. Second, a phenomenon of total fashion pursuit. Consumer in the future are likely to put their goals not in differentiating small item products, but considering various fashion elements based on their individuality and sense of value. Third, world quality-oriented. With the improvement of life level, it accomplishes to emphasize consumers' fashion mind on the world wide popular use of materials, quality, design and brand image. Fourth, with the entrance of neo-rationalism, consumers show increasing trends to emphasize wisdom, solidity in goods strategy pursuing high quality fashion and to demand resonable prices. Fifth, concept-oriented. Consumers are changing into pursuing concept appropriate to individual life scene. Prospecting the composition of the 21st century's fashion market, First, sportive casual zone will draw attention more than any other zone. This is because interest in sports will grow according to the increase of leisure time and the expasion of time and space in the 21st century, and also ecology will become the important issue of sports sense because of human beings's natural habit toward nature. Second, the down aging phenomenon will accelerate its speed as a big trend. Third, a retro phenomenon, a concept contrary to digital and high-tech, will become another big trend for its remake, antique, and classic concept in fashion market with ecology trend. New marketing strategy to cope with changing fashion market is as follows. First, with the trend of borderless concept, borders between apparels are becoming vague, for example, they offer custom-made products to consumers. Second, as more enterprises take the way of gorilla and guerrilla where guerrillas who aim at niche market show up will develop. Basically, they think highly of individual creative study, and pursue the scene adherence with high sensitiveness. However this polarization becomes mutually-supplementing relationship showing gorilla's guerilla movement, and guerilla's gorilla high-tech. Third with the development of value retailing, enterprises pursuing mass merchandising of groups called category killers are expanded and amplified to new product fields, and expand business' share. Fourth, using outsourcing, the trend to use exterior function leaving each enterprise's strength by inspecting its own work is gradually strong. Fifth, with the expansion of none store sale, the entrance of the internet and the CD-ROM sales added to communication sales such as catalogues are specified. An eminent American think tank expect that 5-5% of the total sale of clothes and home goods in 2010 will be done by none store sale. Accordingly, to overcome the problems, First international, global level marketing, Second, the improvement of technology, Third, knowledge-creating marketing are needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.881-893
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• 2007

IT(Information Technology)-based industries have caused a recent digital revolution and the appearance of various types' information service, being largely expanded toward info-communication device company, info-communication service company, software company etc.. Therefore, the needs to evaluate the company value of IT business for M&A or liquidation are growing tremendously. Unlike other industries, however, IT industry has a short lift cycle and so it doesn't have not only a company value-evaluating model for general businesses but the objective one for IT companies yet. So, this thesis analyzes various value-evaluating technique and newly rising ROV. DCF, the change method of company's cash flow including tangible assets into future value, had been applied during the past industrialization economy era and has been persuasively applied to the present. However, the DCF valuation has no option but to make many mistakes because IT companies have more intangible assets than tangible assets. Accordingly, it is ROV, recognized as the new method of evaluating companies' various options normally and quantitatively, that is brought up recently. But the evaluation on the companies' various options is too subjective and theoretical up to now and due to the lack of objective ground and options, it's not possible to be applied to reality. In this thesis, it is found that ROV is more accurate than DCF, comparing DCF and ROV through four examples. As the options applied to ROV are excessively limited, we tried to develop ROV into a new method by deriving five invisible value factors within IT companies. Therefore, on this occasion, we should set up the basic valuation methods on IT companies and should research and develop an effective and various valuation methods suitable to each company like an internet-based company, a S/W developing enterprise, a network-related company among IT companies.

• The Korean Journal of Archival Studies
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• no.1
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• pp.23-76
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• 2000

In this paper, I examined what have been researched and determined about preservation strategy and selection of preservation media in the western archival community. Archivists have primarily been concerned with 'preservation' and 'use' of archival materials worth of being preserved permanently. In the new information era, preservation and use of archival materials were faced with new challenge. Life expectancy of paper records was shortened due to acidification and brittleness of the modem papers. Also emergence of information technology affects the traditional way of preservation and use of archival materials. User expectations are becoming so high technology-oriented and so complicated as to make archivists act like information managers using computer technology rather than traditional archival handicraft. Preservation strategy plays an important role in archival management as well as information management. For a cost-effective management of archives and archival institutions, preservation strategy is a must. The preservation strategy encompasses all aspects of archival preservation process and practices, from selection of archives, appraisal, inventorying, arrangement, description, conservation, microfilming or digitization, archival buildings, and access service. Those archival functions should be considered in their relations to each other to ensure proper preservation of archival materials. In the integrated preservation strategy, 'preservation' and 'use' should be combined and fulfilled without sacrificing the other. Preservation strategy planning is essential to determine the policies of archives to preserve their holdings safe and provide people with a maximum access in most effective ways. Preservation microfilming is to ensure permanent preservation of information held in important archival materials. To do this, a detailed standardization has been developed to guarantee the permanence of microfilm as well as its product quality. Silver gelatin film can last up to 500 years in the optimum storage environment and the most viable option for permanent preservation media. ISO and ANIS developed such standards for the quality of microfilms and microfilming technology. Preservation microfilming guidelines was also developed to ensure effective archival management and picture quality of microfilms. It is essential to assess the need of preservation microfilming. Limit in resources always put a restraint on preservation management. Appraisal (and selection) of what to be preserved was the most important part of preservation microfilming. In addition, microfilms with standard quality can be scanned to produce quality digital images for instant use through internet. As information technology develops, archivists began to utilize information technology to make preservation easier and more economical, and to promote use of archival materials through computer communication network. Digitization was introduced to provide easy and universal access to unique archives, and its large capacity of preserving archival data seems very promising. However, digitization, i.e., transferring images of records to electronic codes, still, needs to be standardized. Digitized data are electronic records, and st present electronic records are very unstable and not to be preserved permanently. Digital media including optical disks materials have not been proved as reliable media for permanent preservation. Due to their chemical coating and physical character using light, they are not stable and can be preserved at best 100 years in the optimum storage environment. Most CD-R can last only 20 years. Furthermore, obsolescence of hardware and software makes hard to reproduce digital images made from earlier versions. Even if when reformatting is possible, the cost of refreshing or upgrading of digital images is very expensive and the very process has to be done at least every five to ten years. No standard for this obsolescence of hardware and software has come into being yet. In short, digital permanence is not a fact, but remains to be uncertain possibility. Archivists must consider in their preservation planning both risk of introducing new technology and promising possibility of new technology at the same time. In planning digitization of historical materials, archivists should incorporate planning for maintaining digitized images and reformatting them in the coming generations of new applications. Without the comprehensive planning, future use of the expensive digital images will become unavailable. And that is a loss of information, and a final failure of both 'preservation' and 'use' of archival materials. As peter Adelstein said, it is wise to be conservative when considerations of conservations are involved.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.73-85
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• 2004

Recently, as the growth of the wireless Internet, PDA and HPC, the focus of research and development related with GIS(Geographic Information System) has been changed to the Real-Time Mobile GIS to service LBS. To offer LBS efficiently, there must be the Real-Time GIS platform that can deal with dynamic status of moving objects and a location index which can deal with the characteristics of location data. Location data can use the same data type(e.g., point) of GIS, but the management of location data is very different. Therefore, in this paper, we studied the Real-Time Mobile GIS using the HBR-tree to manage mass of location data efficiently. The Real-Time Mobile GIS which is developed in this paper consists of the HBR-tree and the Real-Time GIS Platform HBR-tree. we proposed in this paper, is a combined index type of the R-tree and the spatial hash Although location data are updated frequently, update operations are done within the same hash table in the HBR-tree, so it costs less than other tree-based indexes Since the HBR-tree uses the same search mechanism of the R-tree, it is possible to search location data quickly. The Real-Time GIS platform consists of a Real-Time GIS engine that is extended from a main memory database system. a middleware which can transfer spatial, aspatial data to clients and receive location data from clients, and a mobile client which operates on the mobile devices. Especially, this paper described the performance evaluation conducted with practical tests if the HBR-tree and the Real-Time GIS engine respectively.