• (The) Research of the performance art and culture
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• no.20
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• pp.129-161
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• 2010

Women's social status is marginal in the patriarchal system, therefore it is not easy to express their's desire. Women's social role are restricted by the Confucian culture in the late of Chosun Dinasty. But women freely expressed their's gamseong(感性) by singing the folk songs. Many researches have focused on the reality of life or the structure and meanings of the women's folk songs. On the contrary, no one has paid attention to the gamseong in the women's folk songs. This is the reason why this thesis focused on the aspects of gamseong in the women's folk songs. The aspect of gamseong expression in women's folk songs can be classfied as follow: HAN(恨) resulting from living with one's husband's parents (Si-jip-sa-ri); LONGING caused by parting with the lover; HOPE due to childbirth and bringing up; SHIN-MYOUNG(神明) through deviation and liberation. In conclusion, We can find out women's gamseong would be formed from the their own roles and relationship with the others. Besides they could offset their sorrow and cure their pain through loving others and selfloving.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• (The) Research of the performance art and culture
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• no.42
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• pp.147-181
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• 2021

Dalgubal drum dance is inherited in a recreated form by incorporating regional symbolism and the dance philosophy and artisticity of Young Hwangbo, the creator, based on the traditional drum dance of the Yeongnam region. This dance having popularity with the transformation of traditional Korean culture has been invited not only to Yeongnam region including Daegu but also to international various venues. This study explores what the movement characteristics of this Dalgubal drum dance are and the unique charm and symbolic meaning of this dance. Specific analysis was conducted through analyzing Dalgubal drum dance video film of the 89th Korean Myeongmujeon's by using Laban Movement Analysis as a research method. The special features of this dance resulted from the LMA analysis in terms of the four categories-Body, Effort, Shape, and Space-reveal simple yet cheerful personalities and strong yet patient characteristics of the people in Daegu. The harmony of drum sounds(music) and movements(dance) creates various characteristics of dances and reveals the beauty and excitement of unique Korean dance. In particular, drum play and its related dance movements create curved linear spatial pattern of arm movements, Spiral Shape in body posture, and diverse floor patterns occupying whole stage space. These movements show the three-dimensional spatial beauty and the artistic ideas for recreation of traditional drum dance, which considered with the spatial structure of the proscenium stage. In addition, the well-organized structure and harmonious movements of this dance show the traditional Korean philosophy, implying heaven, earth, and human being and the wholeness, and the harmony of yin and yang. The dance aims at communication between the audiences and dancers through sharing excitement and the aesthetic beauty of dance. This can be interpreted as a meaningful expression of traditional Korean philosophy developed with the unique value and characteristics of Korean dance.

• (The) Research of the performance art and culture
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• no.38
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• pp.71-109
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• 2019

In this study, succession aspects of direction structure and dancing were reviewed in Moondoong drum dance succeeded by Yong Bae Cho of Goseong Ogwangdae. Sung Rak Hong who succeeded to Moondoong drum dance before Yong Bae Cho directed only 'drum dance' mainly with Goodguri rhythm. While Sung Rak Hong succeeded, the drum of Moondoong Gwangdae became smaller, which was changed from drum before 1965, to semi-drum in 1966 and tabor in 1967 and thereafter. Yong Bae Cho succeeded to Moondoong drum dance since 1970, adding 'Moondoong dance' directing tabor at the floor together with 'drum dance' before August 1972 and directing Dutbaegi rhythm. From the first succession of Goseong Ogwangdae since the winter in 1974, obscene movements were disappeared, and the setting with Yangban and contents to sublimate resentment were added in Moondoong drum dance. These changes seemed to be affected by succession format of Tongyoung Ogwangdae Moondoong drum dance and Ok Jin Gong's idiot dance. There are succession patterns when reviewing Moondoong drum dance directed by Yong Bae Cho. In case of 'Moondoong' dance, repeated forms were succeeded including 'fixed dance'->'impromptu dance'->'jump' in center of three fixed dances. In case of 'drum dance,' repeated forms were succeeded including 'fixed dance'->'rolling tabor'->'concluding' -> 'impromptu dance'->'jump' in center of four fixed dances. In 'drum dance' by Yong Bae Cho, many parts of succeeded dance by Sung Rak Hong who was a prior successor were remained. After Yong Bae Cho's death, Jong Bok Heo summarized the dance with more completed order focusing on the structure of Moondoong drum dance succeeded by Yong Bae Cho. Since then, multiple scenes were added continuously including hobbled appearance by Jong Won Heo, happy scene eating barley and scene to catch tabor stick difficultly, by Chang Ryol Heo. Yong Bae Cho added 'Moondoong dance' to the prior works only with 'drum dance' and started adding the story with resentment. The direction structure summarized by Yong Bae Cho became the basic framework in which the following directors added the scenes very easily. Like this, Yong Bae Cho was an excellent director of Goseong Ogwangdae who inherited Moondoong drum dance from the previous generation to establish and develop to hand over the next generations.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• (The) Research of the performance art and culture
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• no.38
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• pp.349-383
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• 2019

This discussion is focused on Donghaeanbyulsingut's 'gutchum-pan to pray'. 'Gutchum-pan to pray' is repeated in almost all of the geori in Byulsingut, so it is a crucial chum-pan that can never be disregarded in understanding Byulsingutchum. Meanwhile, it supposes that Donghaeanbyulsingut is grounded on the activity of producing 'praying (words) and dance (motions)' within its relationship with the structure of capitalistic society along with the context of traditional rituals. The motion that is newly generated as a response to the concrete expression of 'praying' conducted by a mudang (a shaman), that is, the expression coming from the inside associated with the praying is seen as gutchum. This dance is bound to be in competition and interest among shaman groups, and they tend to influence one another. If praying leads to dance, a mudang can gain profits from capital as well as the value of labor. When the mudang succeeds in forming a bigger bond of sympathy with her praying, the object of praying gets more eager to select byulbi and dances a heoteunchum (impromptu dance) more vigorously. This means that a mudang's ability to perform a ritual is associated with the object of praying's consumption. With his impromptu motions, the object of praying comes to go into 'the field of consumption' within the structure of capitalistic competition before he is aware of it. Behind the communication that praying leads to dance, a lot of things are associated with one another organically. 'Gutchum-pan to pray' is generated by the continuous movement of diversity and unity that the time has within the ritual of the mudang and the object of praying. It continues to create the future 'self' that is different from the present 'self', and it means that he expects variability from the present 'self' through 'gutchum-pan to pray'. The mudang also prays for him arranging the variability of the other (the object of praying) inside her labor. In a big picture, of course, the mudang expects the variability of herself, too, which is connected to the value of her labor. The variability that they expect forms a crucial axis that determines where the flow of time and space that the 'gutchum-pan to pray' has is directed to. The contents of praying are directly related with the villagers' lives, and what leads to dance is mostly related with their jobs. This implies that what the mudang experiences in her everyday consuming activity is directly associated with the villagers' activity for earning money. In other words, the contents of that praying change constantly according to the flow of capitalistic economy. Also, those striving to respond to it before anyone else also expect better life for them by substituting their self to the 'gutchum-pan to pray' eagerly. If so, who are the ones that generate 'gutchum-pan to pray'? This can be understood through relationship among mudangs, relationship between the mudang and villagers, and also relationship among villagers. Their relationships can never be free from the concepts like labor in capitalistic society, consumption and expenditure, or time; therefore, they come to compete with the other, the present self, or the better self within the diverse relationships. This gets to be expressed in any ways, words or motions. And the range that covers the creation of either group or individual 'gutchum-pan to pray' in the village is the village community. Outside the range, it is upsized to the competition of the village unit, so individual praying may become diminished more easily. Although mudangs pray in each geori, it does not mean all praying leads to dance. Within various relationships between mudangs and villagers, 'gutchum-pan to pray' comes to be generated, repeated, and extinct. As it is mitigated to more positive competition, it does not lead to gutchum any longer. In other words, repeating 'gutchum-pan to pray' previously created has turned the object of praying into the state different from the former. Also, the two groups both have experienced the last step of Byulsingut, and at that point, praying does no longer lead to dance. In other words, from the position of the shaman group, it is the finish of their labor time and ritual performance, and from the perspective of the villagers, it means the finish of consuming activity and participation in a ritual. The characteristics of 'gutchum-pan to pray' can be summarized as follows. First, it goes through the following process: competition in the village group → competition in the group → competition among individuals. Second, repeated praying does not lead to 'gutchum'. Third, in the cases of praying for each of the occupation groups, the mudang can induce a bond of sympathy from the objects of praying directly, and this lead to dance. Fourth, the group that fails in being included in the category of praying gets to be alienated from 'gutchum-pan to pray' repeatedly.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.