• Title/Summary/Keyword: Newsgroup

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On the study of Usenet service authentication (유즈넷 서비스 인증에 관한 연구)

  • 이달원;조인준;황일선
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.05a
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    • pp.481-484
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    • 2002
  • News service provide professional knowledge which can't be gained from any other internet service and the only way to keep pace with professional group. To get this advantage, many country provide news service and three major korean news server connected with foreign news server provide many articles to korea. A lot of institutes - company, research centers and universities - forward articles to home and abroad. In spite of this important effect, The user of news service and technical supports grow smaller. And now It is necessary for a nation to support and operate by non-profitable business. Especially, partially adapted security weaken entire system safety and can't satisfy service provider of various necessary condition. In this paper, we will mention troubles in authentication and suggest safety authentication method which must be supported by established news service.

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Toward a Social Sciences Methodology for Electronic Survey Research on the Internet or Personal Computer check (사회과학 연구에 있어 인터넷 및 상업용 통신망을 이용한 전자설문 조사방법의 활용)

  • Hong Yong-Gee;Lee Hong-Gee;Chae Su-Kyung
    • Management & Information Systems Review
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    • v.3
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    • pp.287-316
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    • 1999
  • Cyberspace permits us to more beyond traditional face-to-face, mail and telephone surveys, yet still to examine basic issues regarding the quality of data collection: sampling, questionnaire design, survey distribution, means of response, and database creation. This article address each of these issues by contrasting and comparing traditional survey methods(Paper-and-Pencil) with Internet or Personal Computer networks-mediated (Screen-and-Keyboard) survey methods also introduces researchers to this revolutionary and innovative tool and outlines a variety of practical methods for using the Internet or Personal Computer Networks. The revolution in telecommunications technology has fostered the rapid growth of the Internet all over the world. The Internet is a massive global network and comprising many national and international networks of interconnected computers. The Internet or Personal Computer Networks could be the comprehensive interactive tool that will facilitate the development of the skills. The Internet or Personal Computer Networks provides a virtual frontier to expand our access to information and to increase our knowledge and understanding of public opinion, political behavior, social trends and lifestyles through survey research. Comparable to other technological advancements, the Internet or Personal Computer Networks presents opportunities that will impact significantly on the process and quality of survey research now and in the twenty-first century. There are trade-offs between traditional and the Internet or Personal Computer Networks survey. The Internet or Personal Computer Networks is an important channel for obtaining information for target participants. The cost savings in time, efforts, and material were substantial. The use of the Internet or Personal Computer Networks survey tool will increase the quality of research environment. There are several limitations to the Internet or Personal Computer Network survey approach. It requires the researcher to be familiar with Internet navigation and E-mail, it is essential for this process. The use of Listserv and Newsgroup result in a biased sample of the population of corporate trainers. However, it is this group that participates in technology and is in the fore front of shaping the new organizations of interest, and therefore it consists of appropriate participants. If this survey method becomes popular and is too frequently used, potential respondents may become as annoyed with E-mail as the sometimes are with mail survey and junk mail. Being a member of the Listserv of Newsgroup may moderate that reaction. There is a need to determine efficient, effective ways for the researcher to strip identifiers from E-mail, so that respondents remain anonymous, while simultaneously blocking a respondent from responding to a particular survey instrument more than once. The optimum process would be on that is initiated by the researcher : simple, fast and inexpensive to administer and has credibility with respondents. This would protect the legitimacy of the sample and anonymity. Creating attractive Internet or Personal Computer Networks survey formats that build on the strengths of standardized structures but also capitalize on the dynamic and interactive capability of the medium. Without such innovations in survey design, it is difficult to imagine why potential survey respondents would use their time to answer questions. More must be done to create diverse and exciting ways of building an credibility between respondents and researchers on the Internet or Personal Computer Networks. We believe that the future of much exciting research is based in the Electronic survey research. The ability to communicate across distance, time, and national boundaries offers great possibilities for studying the ways in which technology and technological discourse are shaped. used, and disseminated ; the many recent doctoral dissertations that treat some aspect of electronic survey research testify to the increase focus on the Internet or Personal Computer Networks. Thus, scholars should begin a serious conversation about the methodological issues of conducting research In cyberspace. Of all the disciplines, Internet or Personal Computer Networks, emphasis on the relationship between technology and human communication, should take the lead in considering research in the cyberspace.

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A Semantic Text Model with Wikipedia-based Concept Space (위키피디어 기반 개념 공간을 가지는 시멘틱 텍스트 모델)

  • Kim, Han-Joon;Chang, Jae-Young
    • The Journal of Society for e-Business Studies
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    • v.19 no.3
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    • pp.107-123
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    • 2014
  • Current text mining techniques suffer from the problem that the conventional text representation models cannot express the semantic or conceptual information for the textual documents written with natural languages. The conventional text models represent the textual documents as bag of words, which include vector space model, Boolean model, statistical model, and tensor space model. These models express documents only with the term literals for indexing and the frequency-based weights for their corresponding terms; that is, they ignore semantical information, sequential order information, and structural information of terms. Most of the text mining techniques have been developed assuming that the given documents are represented as 'bag-of-words' based text models. However, currently, confronting the big data era, a new paradigm of text representation model is required which can analyse huge amounts of textual documents more precisely. Our text model regards the 'concept' as an independent space equated with the 'term' and 'document' spaces used in the vector space model, and it expresses the relatedness among the three spaces. To develop the concept space, we use Wikipedia data, each of which defines a single concept. Consequently, a document collection is represented as a 3-order tensor with semantic information, and then the proposed model is called text cuboid model in our paper. Through experiments using the popular 20NewsGroup document corpus, we prove the superiority of the proposed text model in terms of document clustering and concept clustering.

Improving Naïve Bayes Text Classifiers with Incremental Feature Weighting (점진적 특징 가중치 기법을 이용한 나이브 베이즈 문서분류기의 성능 개선)

  • Kim, Han-Joon;Chang, Jae-Young
    • The KIPS Transactions:PartB
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    • v.15B no.5
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    • pp.457-464
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    • 2008
  • In the real-world operational environment, most of text classification systems have the problems of insufficient training documents and no prior knowledge of feature space. In this regard, $Na{\ddot{i}ve$ Bayes is known to be an appropriate algorithm of operational text classification since the classification model can be evolved easily by incrementally updating its pre-learned classification model and feature space. This paper proposes the improving technique of $Na{\ddot{i}ve$ Bayes classifier through feature weighting strategy. The basic idea is that parameter estimation of $Na{\ddot{i}ve$ Bayes considers the degree of feature importance as well as feature distribution. We can develop a more accurate classification model by incorporating feature weights into Naive Bayes learning algorithm, not performing a learning process with a reduced feature set. In addition, we have extended a conventional feature update algorithm for incremental feature weighting in a dynamic operational environment. To evaluate the proposed method, we perform the experiments using the various document collections, and show that the traditional $Na{\ddot{i}ve$ Bayes classifier can be significantly improved by the proposed technique.

Text Classification Using Heterogeneous Knowledge Distillation

  • Yu, Yerin;Kim, Namgyu
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.10
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    • pp.29-41
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    • 2022
  • Recently, with the development of deep learning technology, a variety of huge models with excellent performance have been devised by pre-training massive amounts of text data. However, in order for such a model to be applied to real-life services, the inference speed must be fast and the amount of computation must be low, so the technology for model compression is attracting attention. Knowledge distillation, a representative model compression, is attracting attention as it can be used in a variety of ways as a method of transferring the knowledge already learned by the teacher model to a relatively small-sized student model. However, knowledge distillation has a limitation in that it is difficult to solve problems with low similarity to previously learned data because only knowledge necessary for solving a given problem is learned in a teacher model and knowledge distillation to a student model is performed from the same point of view. Therefore, we propose a heterogeneous knowledge distillation method in which the teacher model learns a higher-level concept rather than the knowledge required for the task that the student model needs to solve, and the teacher model distills this knowledge to the student model. In addition, through classification experiments on about 18,000 documents, we confirmed that the heterogeneous knowledge distillation method showed superior performance in all aspects of learning efficiency and accuracy compared to the traditional knowledge distillation.