• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.22-29
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• 2009

In previous work, anomaly-based intrusion detection techniques have been widely used to effectively detect various intrusions into a computer. This is because the anomaly-based detection techniques can effectively handle previously unknown intrusion methods. However, most of the previous work assumed that the normal network connections are fixed. For this reason, a new network connection may be regarded as an anomalous event. This paper proposes a new anomaly detection method based on an association-mining algorithm. The proposed method is composed of two phases: intra-packet association mining and inter-packet association mining. The performances of the proposed method are comparatively verified with JAM, which is a conventional representative intrusion detection method.

• Journal of Internet Computing and Services
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• v.4 no.1
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• pp.39-52
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• 2003

As software is developed for many applications and software defects have caused serious problem sin those applications, the concern of software quality evaluation increases rapidly. Although there has been many efforts for establishing standards for software evaluation, such as ISO/IEC 9126, they provide only a framework for defining quality characteristics and evaluation process. They, however, do not provide practical guidances for deriving resonable weight value criteria for software evaluation. This paper presents a method to draw quantitative weight values from evaluator's subjective data in the process of software evaluation as observing the ISO/IEC 9126 standard. To eliminate the evaluators' subjectiveness and the uncertainty of weight value during evaluation, the Dempster-Shafer (D-S) theory is adopted and utilized. In this paper, the D-S theory is supplemented with an improved merge rule to reduce the bias of weight value when they are merged with other evaluator's weight value. The proposed merge rule has been tested and proved with actual evaluation data.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.169-179
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• 2005

Standard industry and occupation code are usually assigned manually in Korean census. The manual coding is very labor intensive and expensive task. Furthermore, inconsistent coding is resulted from the ability of human experts and their working environments. This paper proposes an automatic code classification system which converts natural language responses on survey questionnaires into corresponding numeric codes by using manually constructed rule base and example-based machine learning. The system was trained with 400,000 records of which standard codes was assigned. It was evaluated with 10-fold cross validation and was tested with three code sets: population occupation set, industry set, and industry survey set. The proposed system showed 76.63%, 82.24 and 99.68% accuracy for each code set.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.155-167
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• 2006

It is desirable if users surfing on the Internet could find Web pages related to their interests as closely as possible. Toward this ends, this paper presents a topic specific Web crawler computing the degree of relevance. collecting a cluster of pages given a specific topic, and refining the preliminary set of related web pages using term frequency/document frequency, entropy, and compiled rules. In the experiments, we tested our topic specific crawler in terms of the accuracy of its classification, crawling efficiency, and crawling consistency. First, the classification accuracy using the set of rules compiled by CN2 was the best, among those of C4.5 and back propagation learning algorithms. Second, we measured the classification efficiency to determine the best threshold value affecting the degree of relevance. In the third experiment, the consistency of our topic specific crawler was measured in terms of the number of the resulting URLs overlapped with different starting URLs. The experimental results imply that our topic specific crawler was fairly consistent, regardless of the starting URLs randomly chosen.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.559-568
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• 2014

Previous polarity classification using sentiment analysis utilizes a sentence rule by product reviews based rating points. It is difficult to be applied to blogs which have not rating of product reviews and is possible to fabricate product reviews by comment part-timers and managers who use web site so it is not easy to understand a product and store reviews which are reliability. Considering to these problems, if we analyze blogs which have personal and frank opinions and classify polarity, it is possible to understand rightly opinions for the product, store. This paper suggests that we extract high frequency vocabularies in blogs by several domains and choose topic words. Then we apply a technique of sentiment analysis and classify polarity about contents of blogs. To evaluate performances of sentiment analysis, we utilize the measurement index that use Precision, Recall, F-Score in an information retrieval field. In a result of evaluation, using suggested sentiment analysis is the better performances to classify polarity than previous techniques of using the sentence rule based product reviews.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.727-736
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• 2014

The fundamental concerns of this paper are to analyze the effects of some characteristics on the employment of new college graduated students in viewpoint of data visualization. We use individual and department characteristic data of K-university graduated students in 2010. We apply multiple correspondence analysis, decision tree analysis, association rules and social network analysis for data visualization. The results of the analysis are summarized as follows. First, an analysis of the determinants of employment shows that GPA, department category, age and number of majors, recruiting time affect the employment rate. Second, higher GPA and natural category of department positively affect the employment rate. Finally, low age, single major and early recruiting time also positively affect the employment rate.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.13 no.2
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• pp.139-148
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• 2001

Phenomena induced by waves, such as overtopping, sediment transport, vibration/fluctuation and destruction of structures are highly influenced by the directionality of wave propagation. These phenomena are often dominated by non-linearity, and so hydraulic model experiments are widely adopted for stability analysis rather than numerical modeling, Thus, stability ofrubblc mound breakwaters(RMB) due to wavc directionality was experimentally investigated in this study. The incident wave angle $30^{\circ}$ was found more risky on the damage rate of RMB under directional regular waves, and the incident wave angle $40^{\circ}$ was found relatively risky under directional irregular waves. These results clarified the wave directionality effect on the stability ofRMB, These facts were found correspondent to the occurrence of the peak between $20^{\circ}$-$40^{\circ}$ with the directional frequency distribution of lIlO maximum water particle velocity.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.3
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• pp.141-147
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• 2006

A newly designed floating breakwater made of Polyethylene with considering the introduction of new material for being harmony with environment and stability of the floater is developed for a marine ranching. In this study, the new concept in which incident wave dissipates its energy due to the vortex shedding by passing through the pipes and sheets is selected for wave breaking mechanism. Model experiment in order to te st its capability is performed for the regular and irregular waves in ocean engineering basin. Good capability to break the incident wave within the 6 seconds of period and 1 m of height is shown. Breaking efficiency for long period wave is not so good in regular and irregular wave. The results of this study will contribute to the design and construction of the floating breakwater.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.9-17
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• 2012

War-game simulation models the situation of a battlefield and has been used for evaluating fighting power and analyzing the occupation of a troop. However, in war-game simulation environment, it is very complex to consider all factors which can be influenced in real battlefields. To solve the problem of the consideration, we propose an ontology-based path finding model. This model uses an ontology to conceptualize the situation data of a battlefield and represents the relations among the concepts. In addition, we extract new knowledge from the war-game ontology by defining some inference rules and share knowledge by the established rules. For the performance evaluation of the proposed model, we made a limitation on the simulation environment and measure the moving time of a troop, the fighting capability of a troop, and the necessary cost while a troop is moving. Experimental results show that this model provides many advantages in aspects of the moving time, a loss of fighting capability, and the necessary cost.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.407-414
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• 2002

In this paper, we present a method that automatically generates concatenate morpheme based language models to improve the performance of Korean large vocabulary continuous speech recognition. The focus was brought into improvement against recognition errors of monosyllable morphemes that occupy 54% of the training text corpus and more frequently mis-recognized. Knowledge-based method using POS patterns has disadvantages such as the difficulty in making rules and producing many low frequency concatenate morphemes. Proposed method automatically selects morpheme-pairs from training text data based on measures such as frequency, mutual information, and unigram log likelihood. Experiment was performed using 7M-morpheme text corpus and 20K-morpheme lexicon. The frequency measure with constraint on the number of morphemes used for concatenation produces the best result of reducing monosyllables from 54% to 30%, bigram perplexity from 117.9 to 97.3. and MER from 21.3% to 17.6%.