• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.593-598
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• 2003

Machine learning organizes knowledge for efficient and accurate reuse. This paper is concerned with methods of concept learning from examples, which glean knowledge from a training set of preclassified ‘objects’. Ideally, training facilitates classification of novel, previously unseen objects. However, every learning system relies on processing and representation assumptions that may be detrimental under certain circumstances. We explore the biases of a well-known learning system, ID3, review improvements, and introduce some improvements of our own, each designed to yield accurate and pedagogically sound classification.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.138-140
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• 1999

분류기법은 과거데이터를 분석하여 새로운 데이터에 대한 예측에 사용되며, 결정트리 알고리즘을 많이 사용한다. 따라서, 이 기법은 전자상거래에서 DB 마케팅을 위해 데이터베이스에 저장되어 있는 고객데이터를 분석하여 암시적인 고객들의 행위규칙을 찾고, 예측하기 위하여 사용할 수 있다. 기존의 분류알고리즘들은 전자상거래에서 일반적인 연속형 고객데이터를 처리하는데는 많은 문제점을 가지고 있다. 이러한 문제를 해결하기 위하여 연속형 데이터를 범주형 데이터로 변환하는 알고리즘을 구현하였다. 이 논문은 전자상거래에 적용하기 위한 고객분류기로서 ID3 알고리즘에 1차원 클러스터링알고리즘을 결합하여 사용한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1447-1452
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• 2022

Seoul Special City, one of the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. Small business owners in these manufacturing clusters have developed in the form of mutual assistance. Due to the nature of the agglomeration site, each process is handled by an individual company. It is difficult for relatively small business owners to prepare order processing services that provide real-time logistics movement information between processes. This paper collects and analyzes existing logistics data for smooth order and delivery of small business owners in package manufacturing and special printing fields We design an artificial intelligence Fulfillment Service Platform system with CRNN, k-NN, and ID3 Decision Tree Algorithm. Through this study, it is expected that it will greatly contribute to increasing sales and improving capabilities by allowing small business owners in integrated areas to use individual orders and delivery customized services through the Cloud network.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.345-349
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• 2009

Social bookmarking systems are a typical web 2.0 service based on folksonomy, providing the platform for storing and sharing bookmarking information. Spammers in social bookmarking systems denote the users who abuse the system for their own interests in an improper way. They can make the entire resources in social bookmarking systems useless by posting lots of wrong information. Hence, it is important to detect spammers as early as possible and protect social bookmarking systems from their attack. In this paper, we applied a diverse set of machine learning approaches, i.e., decision tables, decision trees (ID3), $na{\ddot{i}}ve$ Bayes classifiers, TAN (tree-augment $na{\ddot{i}}ve$ Bayes) classifiers, and artificial neural networks to this task. In our experiments, $na{\ddot{i}}ve$ Bayes classifiers performed significantly better than other methods with respect to the AUC (area under the ROC curve) score as veil as the model building time. Plausible explanations for this result are as follows. First, $na{\ddot{i}}ve$> Bayes classifiers art known to usually perform better than decision trees in terms of the AUC score. Second, the spammer detection problem in our experiments is likely to be linearly separable.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.522-527
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• 2008

Socially Intelligent agent is the agent not only having the ability to recognize and to process human affect through learning and adaptation, but also having human-like social intelligence. By making human feel familiar with the computer, the agent is expected to enhance human-computer interaction (HCI) by providing users with the personalized services and interfaces. This paper proposes the framework for socially intelligent agents behaving socially according to the emotions recognized by ID3 algorithm and psychological OCC model. Also, the agent could process with the emotion to make socially intelligent response through three layered affect functioning model. Finally, the proposed agent can be applied for the development and application of socially intelligent agent in wide areas as the agent framework having similar affect and cognitive structure with human being.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.1-9
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• 2010

In recent year, the cores of ubiquitous environment are sensor networks and RFID systems. RFID system transmits the electronic information of the tag to the reader by using RF signal. Collision happens in RFID system when there are many matched tags, and it degrades the tag identification performance. Such a system needs algorithm which is able to arbitrate tag collision. This paper suggests a hybrid method which reduces collision between the tags, and can quickly identify the tag. The proposed method operates based on certainty, which takes an advantage of tree based algorithm, and to reduce collision it selects transmission time slot by using tag ID. The simulation results show the suggested method has higher performance in the number of queries and collision compared to other tree based and hybrid algorithms.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.61-71
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• 2010

The attributes related to the health condition of RC deck slabs are analyzed to help us identify and rate the safety level of the bridges in this study. According to the related reports the state assessment for the outward aspects of bridges is the important and critical part for rating the overall structural safety. In this respect, the careful identification for the various state attributes make the field inspection and structural diagnosis very effective. This study analyzes the influence of the state attributes on evaluation classes and the relationship of them by the inductive reasoning, which raise the understanding and performance for evaluation work, and support the logical approach for the state assessment. ID3 algorithm applied to the case set which is constructed from the field reports indicates the main attributes and the precedence governing the assessment, and derives the decision hierarchy for the state assessment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.48-55
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• 2009

In this paper, We propose Adaptive Group Separation algorithm for efficient RFID system AGS algorithm determines the optimized initial prefix size j, and divides the group of. A reader requests the group and searches the tag ID. If a tag collision occurred, reader adds a one bit, '0' or '1' at first bit of collision point, As a result we observe that transmitted data bits and the recognition time are decreased. The proposed algorithms have been verified by computer simulation. The performance of the proposed anti-collision algorithm is evaluated in terms of the number of repetitions and the amount of transmission bits according to the in crease of the number of tags is 256. The AGS algorithm improve the number of repetitions by about 32.3% and reduce tile amount of the transmission bits by about 1/40 than slotted binary tree algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.839-850
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• 2014

As the social and financial damages caused by APT attack such as 3.20 cyber terror are increased, the technical solution against APT attack is required. It is, however, difficult to protect APT attack with existing security equipments because the attack use a zero-day malware persistingly. In this paper, we propose a host based anomaly detection method to overcome the limitation of the conventional signature-based intrusion detection system. First, we defined 39 features to identify between normal and abnormal behavior, and then collected 8.7 million feature data set that are occurred during running both malware and normal executable file. Further, each process is represented as 83-dimensional vector that profiles the frequency of appearance of features. the vector also includes the frequency of features generated in the child processes of each process. Therefore, it is possible to represent the whole behavior information of the process while the process is running. In the experimental results which is applying C4.5 decision tree algorithm, we have confirmed 2.0% and 5.8% for the false positive and the false negative, respectively.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.135-141
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• 2008

We propose a new method for recognizing the activities of daily living(ADL) based on the state-dependent motion analysis using 3-axial accelerometers and a glove type RFID reader. Two accelerometers are used for the classification of 5 body states based on the decision tree. Classification of the instrumental activities is performed based on the hand interaction with an object ID using an accelerometer and a RFID reader. Object-dependent hand movements are classified into 5 categories in advance and final decision combines the body state and the instrumental activities. Experiment shows that the suggested hierarchical motion analysis provides accuracy rate of over 90% for all 20 ADLs.