• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.53-64
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• 2002

Association rule discovery is a method that detects associative relationships between items or attributes in transactions. It is one of the most widely studied problems in data mining because it offers useful insight into the types of dependencies that exist in a data set. However, most studies on association rule discovery have the drawback that they can not discover association rules among user groups that have common characteristics. To solve this problem, we segment the set of users into user-subgroups by using feature selection and the user segmentation, thus local association rules in user-subgroup can be discovered. To evaluate that the local association rules are more appropriated than the global association rules in each user-subgroup, derived local association rules are compared with global association rules in terms of several evaluation measures.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.573-578
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• 2008

Recently, we should control various devices such as TV, audio, DVD player, video player, and set-top box simultaneously to manipulate home theater system. To execute the function the user want in this situation, user should know functions and positions of the buttons in several remote controllers. Normally, people feel difficult due to these realistic problems. Besides, the number of the devices that we can control shall increase, and people will confuse more if the ubiquitous home environment is realized. Therefore, user adaptive interface that provides the summarized functions is required. Moreover there can be a lot of mobile and stationary controller devices in ubiquitous computing environment, so user interface should be adaptive in selecting the functions that user wants and in adjusting the features of UI to fit in specific controller. To implement the user and controller adaptive interface, we modeled the ubiquitous home environment and used modeled context and device information. We have used Bayesian network to get the degree of necessity in each situation. Behavior selection network uses predicted user situation and the degree of necessity, and it selects necessary functions in current situation. Selected functions are used to construct adaptive interface for each controller using presentation template. For experiments, we have implemented ubiquitous home environment and generated controller usage log in this environment. We have confirmed the BN predicted user requirements effectively as evaluating the inferred results of controller necessity based on generated scenario. Finally, comparing the adaptive home UI with the fixed one to 14 subjects, we confirmed that the generated adaptive UI was more useful for general tasks than fixed UI.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.88-95
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• 2002

According to an evolution of digital broadcasting, it is possible that terrestrial and satellite broadcasting media provide multi-channel services. CATV and satellite media have been also extended to hundreds of channels. As the result of channel expanding, viewers came to select lots of channels. But it is difficult that they select the favorite channel among hundreds of channels. In this paper, we propose an efficient automatic method to recommend channels and programs on a viewer's preference in a multi-channel broadcasting receiver like a Set ToP Box(STB). The proposed algorithm selects channels based on the following method. It makes and saves user history data by using MPEG-7 MDS based on the program information a viewer had watched. It recommends programs similar to a viewer's preference based on user history data. It selects the channel in the recommended genre based on the viewer's channel preference. The experimental result shows that the proposed scheme is efficient to select the user preference channel.

• Journal of Korean Library and Information Science Society
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• v.40 no.3
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• pp.25-47
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• 2009

The purpose of this study is to analyze ISO/DIS 28560 and to cope with the current developments in library RFID technologies. The user data elements in part 1 and encoding rules in part 2 and part 3 of ISO/DIS 28560 are explored. In addition, a few corresponding cases regarding user data elements on ISO/DIS 28560 are investigated. Based on the corresponding cases, four user data elements are selected. They are , , , and . This study expects to allow fertile ground for discussion on the selection of user data elements in Korea.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.859-868
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• 2004

We propose a method of selecting initial training examples for active learning so that it can reach high accuracy faster with fewer further queries. Our method is based on the assumption that an active learner can reach higher performance when given an initial training set consisting of diverse and typical examples rather than similar and special ones. To obtain a good initial training set, we first cluster examples by using k-means clustering algorithm to find groups of similar examples. Then, a representative example, which is the closest example to the cluster's centroid, is selected from each cluster. After these representative examples are labeled by querying to the user for their categories, they can be used as initial training examples. We also suggest a method of using the centroids as initial training examples by labeling them with categories of corresponding representative examples. Experiments with various text data sets have shown that the active learner starting from the initial training set selected by our method reaches higher accuracy faster than that starting from randomly generated initial training set.

• Information Systems Review
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• v.14 no.3
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• pp.115-129
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• 2012

A matchmaking system is a type of recommender systems that provides a set of dating partners suitable for the user by online. Many matchmaking systems, which are widely used these days, require users to specify their preferences with regards to ideal dating partners based on criteria such as age, job and salary. However, some users are not aware of their exact preferences, or are reluctant to reveal this information even if they do know. Also, users' selection standards are not fixed and can change according to circumstances. This paper suggests a new matchmaking system called Decision Tree based Matchmaking System (DTMS) that automatically adjusts the stated standards of a user by analyzing the characteristics of the people the user chose to contact. AMMS provides recommendations for new users on the basis of their explicit preferences. However, as a user's behavioral records are accumulated, it begins to analyze their hidden implicit preferences using a decision tree technique. Subsequently, DTMS reflects these implicit preferences in proportion to their predictive accuracy. The DTMS is regularly updated when a user's data size increases by a set amount. This paper suggests an architecture for the DTMS and presents the results of the implementation of a prototype.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.8-14
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• 2008

There are two a approaches for the Cognitive Radio(CR) development. One is 'Full CR', which Joseph Mitola III proposed, and another is 'Spectrum CR', which is currently being standardized. The target approach of this paper is the latter and we develop a Cognitive Engine(CE) and simulated a channel set management(CSM), which is a core function of CE. The Channel set management evaluates channel quality and Incumbent User(IU) vacancy possibility and classifies the channel set, which is performed by using channel state history. Especially, a very important function for the channel set management is a channel state prediction and this paper proposed a Hidden Markov Model(HMM) based channel state prediction and a method for increasing performance. Also, we applied the proposed method into our simulator and simulated channel state prediction. Through the simulation, we verified as we applied our proposed scheme, the performance of channel state prediction gets better and through comparing with RS and SS, we verified the HMM based Channel state prediction is better.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.775-793
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• 2023

Human decision-making is a complex behavior. A replication of human decision making offers a potential to enhance the capacity of intelligent systems by providing additional user assistance in decision making. By reducing the effort and task complexity on behalf of the user, such replication would improve the overall user experience, and affect the degree of intelligence exhibited by the system. This paper explores individuals' decision-making processes when using recommender systems, and its related outcomes. In this study, human decision-making (HDM) refers to the selection of an item from a given set of options that are shown as recommendations to a user. The goal of our study was to identify IS constructs that contribute towards such decision-making, thereby contributing towards creating a mental model of HDM. This was achieved through recording Electroencephalographic (EEG) readings of subjects while they performed a decision-making activity. Readings from 16 righthanded healthy avid readers reflect that reward, theory of mind, risk, calculation, task intention, emotion, sense of touch, ambiguity and decision making are the primary constructs that users employ while deciding from a given set of recommendations in an online bookstore. In all 10 distinct brain areas were identified. These brain areas that lead to their respective constructs were found to be cingulate gyrus, precentral gyrus, inferior parietal lobule, posterior cingulate, medial frontal gyrus, anterior cingulate, postcentral gyrus, superior frontal gyrus, inferior frontal gyrus, and middle frontal gyrus (also referred to as dorsolateral prefrontal gyrus (DLPFC)). The identified constructs would help in developing a design theory for enhancing user assistance, especially in the context of recommender systems.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.129-142
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• 2015

The purpose of this study is to suggest an effective regression testing method in order to minimize the scope of test resulting from the modification of software and to prevent mismatch of test case and test objects. As a way to improve the efficiency of regression testing which uses a change-centric testing technique, the method flow is analyzed and grasped through a static analysis based on source code in order to identify modified parts. After the order of priority is set according to the results of user action log-based dynamic analysis on identified regression testing objects, test effect can be raised by adjusting the order of priority using code complexity. Quality assurance coverage can be checked using the user action log suggested in this study, and the progress of test and whether or not each function has been verified can be checked, too. In addition, by minimizing test parts and adjusting the order of test, costs and time can be saved, making it possible to conduct regression testing effectively.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.94-106
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• 2003

In recent years, the production value of Taiwanese mold and die industries have reached to a high peak in 1998, in amount of NT 604 hundred million dollars. But in recent years production value are going down year by year, till year of 2001 the production value have down to NT 394 hundred million dollars. Its main reason might be the major product were following in medium and low price category, the high accuracy and high cost mold and die still rely on import aboard. Therefore how to made the related technical database system on various field to provide the industry user to promote industries competition ability in mold and die is really urgent matter at this moment. In this research, we will offer how to apply the Visual Basic program language to edit a set of more perfect database system of mold and die material selection. At the present time, we have constructed complete Knowledge-Base-System of intelligence for forging mold and die material, the most related data from the existed data, the others are through our additional experimental results. By using this system by the user can got the related and need data easily, we hope it will reduce designing time and cost for mold and die.