• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1275-1292
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• 2021

As a fine-grained classification problem, aspect-level sentiment classification predicts the sentiment polarity for different aspects in context. To address this issue, researchers have widely used attention mechanisms to abstract the relationship between context and aspects. Still, it is difficult to effectively obtain a more profound semantic representation, and the strong correlation between local context features and the aspect-based sentiment is rarely considered. In this paper, a hybrid attention capsule network for aspect-level sentiment classification (ABASCap) was proposed. In this model, the multi-head self-attention was improved, and a context mask mechanism based on adjustable context window was proposed, so as to effectively obtain the internal association between aspects and context. Moreover, the dynamic routing algorithm and activation function in capsule network were optimized to meet the task requirements. Finally, sufficient experiments were conducted on three benchmark datasets in different domains. Compared with other baseline models, ABASCap achieved better classification results, and outperformed the state-of-the-art methods in this task after incorporating pre-training BERT.

• 지능정보연구
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• 제1권1호
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• pp.23-41
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• 1995

Business researchers have traditionally used statistical techniques for classification. In late 1980's, inductive learning started to be used for business classification. Recently, neural network began to be a, pp.ied for business classification. This study reviews the business classification studies, identifies a neural network a, pp.oach as the most powerful classification tool, and discusses the problems and issues in neural network a, pp.ications.

• 전기학회논문지
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• 제64권2호
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• pp.214-221
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• 2015

A new classification system with 9 main categories and 56 subcategories for the Open Korean Knowledge Dictionary is proposed. The classification system setup is to prepare for the standard classification system to be used to manage effectively vast of terminologies which were published in the Open Korean Knowledge Dictionary and is meant to enhance the fifteen-year old classification system for the standard korean great dictionary to match up to the trend of the modern terminology. The new terminology classification system covering all the academic areas such as humanity, sociology, politics, science, medicine, agriculture, engineering, etc, is designed and proposed after investigating several classification systems. The classification system setup procedures follow as ${\circ}$ The classification system is designed and planed by both the classification system and the academic expert. ${\circ}$ Classification system design covers all the academic areas following National Science and Technology standard classification system after investigating several classification systems such as the National Research Foundation, National Science and Technology Standard Act, Ministry of Knowledge Economy. ${\circ}$ Poll and survey is made to collect comments from total 93 members of several academic areas. ${\circ}$ The poll result is reviewed among working group members and utilized to update the new terminology classification system. Reclassifications are made for the around 200,000 terms in electricity, computer, medicine, pharmacy, biology, and economics according to the new terminology classification system.

• 대한안전경영과학회지
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• 제14권3호
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• pp.143-150
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• 2012

In Korea more than 38,000 types of hazardous material(HAZMAT) are distributed, accordingly the accidents during transportation are also increasing. The agencies related to HAZMAT such as Environment Ministry, National Emergency Management Agency and National Police Agency have their own regulations. However, the classification criteria of HAZMAT are different to each other, which causes many problems in response to transportation accidents. In this study the classification standard of HAZMAT and the classification code using CAS number are suggested to manage HAZMAT efficiently. Through efficient management and standard classification of HAZMAT, the rapid and systematic response to transportation accidents related to HAZMAT is expected to be possible.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1336-1342
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• 2022

Risk-informed safety classification of structures, systems and components (SSCs) is very important for ensuring the safety and economic efficiency of nuclear power plants (NPPs). However, previous methods for safety classification of SSCs do not take the plant operating modes or the operational process of SSCs into consideration, thus cannot concentrate on the safety and economic efficiency accurately. In this contribution, a new method for safety classification of SSCs based on the categorization of plant operating modes is proposed, which considers the NPPs operating history to improve the economic efficiencies while maintaining the safety. According to the time duration of plant configurations in plant operating modes, average importances of SSCs are accessed for an NPP considering the operational process, and then safety classification of SSCs is performed for plant operating modes. The correctness and effectiveness of the proposed method is demonstrated by application in an NPP's safety classification of SSCs.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.195-197
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• 2011

This research deals with an issue of preventive medicine in bioinformatics. We can diagnose liver conditions reasonably well to prevent Liver Cirrhosis by classifying liver disorder patients into fatty liver and high risk groups. The classification proceeds in two steps. Classification rules are first built by clustering five attributes (MCV, ALP, ALT, ASP, and GGT) of blood test dataset provided by the UCI Repository. The clusters can be formed by the K-mean method that analyzes multi dimensional attributes. We analyze the properties of each cluster divided into fatty liver, high risk and normal classes. The classification rules are generated by the analysis. In this paper, we suggest a method to diagnosis and predict liver condition to alcoholic patient according to risk levels using the classification rule from the new results of blood test. The K-mean classifier has been found to be more accurate for the result of blood test and provides the risk of fatty liver to normal liver conditions.

• 기술혁신학회지
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• 제9권3호
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• pp.496-513
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• 2006

과학기술부는 국가 과학기술정보의 체계적인 수집, 분석 및 배포를 위해 국가차원에서 국가과학기술종합정보시스템(NTIS)을 구축하고 있다. 성공적인 NTIS의 추진을 위해서는 다양한 정보를 체계적으로 분류하고 유통시킬 수 있는 분류체계가 필요하다. 본 논문에서는 현재의 국가과학기술표준분류와 각 기관의 분류를 상호 연계하는 호환표를 사용하여 NTIS를 구축하는 것이 타당한지에 대하여 분석하였다. 분석결과 현행 분류체계를 이용하는 경우 정보의 유통이 원활하지 못한 것으로 나타나고 있으므로 성공적인 NTIS의 구축을 위해서는 새로운 분류체계가 고려될 필요가 있는 것으로 보인다.

• ETRI Journal
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• 제42권3호
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• pp.311-323
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• 2020

Encrypted traffic classification plays a vital role in cybersecurity as network traffic encryption becomes prevalent. First, we briefly introduce three traffic encryption mechanisms: IPsec, SSL/TLS, and SRTP. After evaluating the performances of support vector machine, random forest, naïve Bayes, and logistic regression for traffic classification, we propose the combined approach of entropy estimation and artificial neural networks. First, network traffic is classified as encrypted or plaintext with entropy estimation. Encrypted traffic is then further classified using neural networks. We propose using traffic packet's sizes, packet's inter-arrival time, and direction as the neural network's input. Our combined approach was evaluated with the dataset obtained from the Canadian Institute for Cybersecurity. Results show an improved precision (from 1 to 7 percentage points), and some application classification metrics improved nearly by 30 percentage points.

• Asian-Australasian Journal of Animal Sciences
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• 제28권4호
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• pp.592-598
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• 2015

Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.

• 한국도서관정보학회지
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• 제39권3호
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• pp.345-368
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• 2008

이 연구는 KDC 제4판 컴퓨터과학분야의 주요 항목들을 개선하기 위한 것이다. 이를 위해 DDC와 NDC 등 기존 주요분류표와 학술진흥재단의 연구분야분류표, 한국과학재단의 과학기술분야분류 및 국가과학기술표준 분류표 등에 대한 비교분석을 실시하였다. 분석결과 KDC 제4판의 컴퓨터과학분야는 총류와 기술과학분야에 분산전개된 것을 004-005에 통합하는 것이 바람직하고, 하위주제 전개의 체계화, 새로운 주제 추가 및 부적절한 주제의 삭제, 이치, 주기의 추가 등이 필요한 것으로 나타났다. 이 연구에서는 이러한 문제들을 해결하기 위한 구체적인 개선방안을 제시하였다.