• Title/Summary/Keyword: Internet Classification

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One-dimensional CNN Model of Network Traffic Classification based on Transfer Learning

  • Lingyun Yang;Yuning Dong;Zaijian Wang;Feifei Gao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.2
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    • pp.420-437
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    • 2024
  • There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.

A Study on the Classification Schemes of Internet Resources in the Fields of the Information & Telecommunications Technology (정보통신기술 분야 인터넷자원의 분류체계에 관한 연구)

  • 이창수
    • Journal of Korean Library and Information Science Society
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    • v.31 no.4
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    • pp.111-138
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    • 2000
  • The lxnpose of this study is to pmvide the basic data for developing rational classification scheme of intemet resources in the fields of the information & telecommunications technology. The coverage of this study is, kt, to dehe the concept of informtion & telecommunications, and also to investigate the division of information & telecommunications technology through the literature, seumd, to analyze the using library classification schemes for internet resources, and thud, to review classi6cation system of the directory search engines. In this study, I w new

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Machine learning-based nutrient classification recommendation algorithm and nutrient suitability assessment questionnaire

  • JaHyung, Koo;LanMi, Hwang;HooHyun, Kim;TaeHee, Kim;JinHyang, Kim;HeeSeok, Song
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.16-30
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    • 2023
  • The elderly population is increasing owing to a low fertility rate and an aging population. In addition, life expectancy is increasing, and the advancement of medicine has increased the importance of health to most people. Therefore, government and companies are developing and supporting smart healthcare, which is a health-related product or industry, and providing related services. Moreover, with the development of the Internet, many people are managing their health through online searches. The most convenient way to achieve such management is by consuming nutritional supplements or seasonal foods to prevent a nutrient deficiency. However, before implementing such methods, knowing the nutrient status of the individual is difficult, and even if a test method is developed, the cost of the test will be a burden. To solve this problem, we developed a questionnaire related to nutrient classification twice, based upon which an adaptive algorithm was designed. This algorithm was designed as a machine learning based algorithm for nutrient classification and its accuracy was much better than the other machine learning algorithm.

IoT Device Classification According to Context-aware Using Multi-classification Model

  • Zhang, Xu;Ryu, Shinhye;Kim, Sangwook
    • Journal of Korea Multimedia Society
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    • v.23 no.3
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    • pp.447-459
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    • 2020
  • The Internet of Things(IoT) paradigm is flourishing strenuously for the last two decades. Researchers around the globe have their dreams to transmute every real-world object to the virtual object. Consequently, IoT devices are escalating exponentially. The abrupt evolution of these IoT devices has caused a major challenge i.e. object classification. In order to classify devices comprehensively and accurately, this paper proposes a context-aware based multi-classification model for devices, which classifies the smart devices according to people's contexts. However, the classification features of contextual data of different contexts are difficult to extract. The deep learning algorithm has the capability to solve this problem. This paper proposes a context-aware based multi-classification model of devices, which classifies the smart devices according to people's contexts.

Guiding Practical Text Classification Framework to Optimal State in Multiple Domains

  • Choi, Sung-Pil;Myaeng, Sung-Hyon;Cho, Hyun-Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.3
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    • pp.285-307
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    • 2009
  • This paper introduces DICE, a Domain-Independent text Classification Engine. DICE is robust, efficient, and domain-independent in terms of software and architecture. Each module of the system is clearly modularized and encapsulated for extensibility. The clear modular architecture allows for simple and continuous verification and facilitates changes in multiple cycles, even after its major development period is complete. Those who want to make use of DICE can easily implement their ideas on this test bed and optimize it for a particular domain by simply adjusting the configuration file. Unlike other publically available tool kits or development environments targeted at general purpose classification models, DICE specializes in text classification with a number of useful functions specific to it. This paper focuses on the ways to locate the optimal states of a practical text classification framework by using various adaptation methods provided by the system such as feature selection, lemmatization, and classification models.

A Study on the Classification Schemes of Internet Resources for Agriculture (농학분야 인터넷자원의 분류체계에 관한 연구)

  • 김정현;문지현
    • Journal of Korean Library and Information Science Society
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    • v.33 no.3
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    • pp.393-413
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    • 2002
  • This study is to suggest a classification system to classify the agricultural information resources on the internet. In the first part, I analyzes KDC's class 520(agriculture science). The second part compares the agricultural classes of Yahoo! Korea with those of Empas search engine. The third part compares the classes of AFFIS with Agri_Directory. Based on the comparative analysis, it proposes a classificatory system for the agricultural information resources on the internet.

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Internet Business Implementation Guidelines for Retailing Using Product Classification Framework

  • Lee, Heeseok;Park, Suyoung;Park, Byounggu
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2001.10a
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    • pp.91-94
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    • 2001
  • The exponential growth of the Internet usage has motivated the launching of many commercial business web sites. Internet as a purchasing medium shows several unique characteristics because of its customer- driven technologies and absence of physical products. Thus, new commercial medium provokes a reclassification of products. Twenty five types of commercial Products are empirically tested in the Internet retailing and found to be grouped into four categories. This classification framework is investigated in the view of involvement and web technology Furthermore, this paper proposes four business web implementation strategies - impressive, simple, sensory, and semantic - based on the product classification. Proposed guidelines on business web might increase customer satisfaction.

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A Study on the Classification Scheme of Internet Resource for Women's Studies (여성학분야 인터넷 자원의 분류체계에 관한 연구)

  • 이란주;성기주;양정하
    • Journal of Korean Library and Information Science Society
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    • v.32 no.3
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    • pp.397-417
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    • 2001
  • The purpose of this study is to suggest the guidelines for developing the effective classification scheme of woman studies on the Internet. In order to do that, fuve search engines and three subject web databases are analyzed based on the characteristics, problems of their classification schemes. In addition their classification schemes are measured in terms of coverage of subject fields and systematic logic. The results suggest the guidelines far classification scheme reflecting the characteristics of women's studies that ice interdisciplinary and multidisciplinary fields.

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Two-dimensional Binary Search Tree for Packet Classification at Internet Routers (인터넷 라우터에서의 패킷 분류를 위한 2차원 이진 검색 트리)

  • Lee, Goeun;Lim, Hyesook
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.6
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    • pp.21-31
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    • 2015
  • The Internet users want to get real-time services for various multi-media applications. Network traffic rate has been rapidly increased, and data amounts that the Internet has to carry have been exponentially increased. A packet is the basic unit in transferring data at the Internet, and packet classification is one of the most challenging functionalities that routers should perform at wire-speed. Among various known packet classification algorithms, area-based quad-trie (AQT) algorithm is one of the efficient algorithms which can lookup five header fields simultaneously. As a representative space decomposition algorithm, the AQT requires a small amount of memory in storing classification rules, but it does not provide high-speed classification performance. In this paper, we propose a new packet classification algorithm by applying a binary search for the codewords of the AQT to overcome the issue of the AQT. Throughout simulation, it is shown that the proposed algorithm provides a better performance than the AQT in the number of rule comparisons with each input packet.

A Practical Scheme for the Classification of On-line Information Resources on Science and Technology (온라인 과학기술정보자원의 분류체계에 대한 실천적 구성방안)

  • Kim, You-Eil;Choi, Sung-Bae;Koo, Young-Duk
    • Journal of Information Management
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    • v.37 no.4
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    • pp.125-139
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    • 2006
  • The advent of the internet has caused a number of changes in production and dissemination of science and technology information(STI). STI was mainly produced in the form of publication before the advent of the internet. The popularization of the internet, however, has induced the mass production and distribution of STI through the internet. In consequence, the importance and usefulness of on-line STI have become on a level with those of published STI. The rapid growth of quantity and quality of on-line STI forces information service organizations try their best for improving the service satisfaction. In an effort to improve the satisfaction, researchers on information management examined the classification of information resources by exploring the counterparts of bibliography and/or web information service. We examined the national standard of the classification related to science and technology and proposed a practical scheme for the classification of on-line STI resources.