• Agribusiness and Information Management
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• v.1 no.1
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• pp.19-36
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• 2009

1999년 이후 농업인 홈페이지 지원사업 실시 이래 2008년까지 농업인이 운영하는 홈페이지는 전국적으로 1만개소에 달하고 있다. 전자상거래를 성공적으로 운영하고 있는 농업인들의 경우 고객관리에 대한 중요성 인식도가 높고, 이를 관리하기 위한 다양한 프로모션을 전개하고 있다. 이번 연구에서는 농촌진흥청에서 진행하고 있는 농업인 전자상거래 사업에 참여하고 있는 농업인을 대상으로 하여 이들의 고객관리에 대한 필요성 인식정도, 고객확보를 위한 활동, 고객관리의 방법, 고객관리의 유형과 기준, 확보된 고객의 관리를 위한 활동 등을 조사하였다. 농업인들은 전자상거래를 수행하면서, 고객과 직접 접하게 되고, 상품의 판매과정에서 고객관리의 필요성을 높게 인식하고 있으며, 블로그 개설 등 온라인 활동으로 폭을 넓혀가고 있음을 확인할 수 있었다. 하지만, 상당수의 농업인들이 고객관리의 필요성 인식에 비해 이를 실천할 구체적 활동방식과 실행 방법에 대해 구체적이지 못하기 때문에, 정부의 시스템 지원과 교육사업에 있어서 새로운 접근이 필요함을 보여주고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1126-1139
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• 1994

This paper proposes an effective recognition system which recognizes the mixed document consisting of handwritten korean/alphanumeric texts and graphic images. In the preprocessing step, an input image is binarized by the proposed thresholding scheme, then graphic and character regions are separated by using connected components and chain codes. Separated Korean characters are merged based on partial recognition and their character types and sized. In the character recognition step, we use the branch and bound algorithm based on DP matching costs to recognize Korean characters. Also we recognize alphanumeric characters using several robust features. Finally we use a dictionary and information of a recognition step to correct wrong recognition results. Computer simulation with several test documents shows what the proposed algorithm recognized effectively handwritten mixed texts.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.152-159
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• 1997

최근 들어 인쇄체 문자 인식 기술의 발전에 힘입어 필기체 한글 인식에 관한 연구가 활발히 진행되고 있다. 인쇄체 문자와는 달리 자연스럽게 필기된 한글 글씨는 동일한 문자라 하더라도 같은 모양을 가지고 있다고 단정하는 것이 불가능할 정도로 필기자의 필기 유형에 따른 다양한 변형을 내포하고 있다. 따라서 효과적인 한글 글씨 인식기를 개발하기 위해서는 다양한 변형을 포함하는 대용량의 한글 글씨 영상 데이터베이스가 필수적이다. 본 논문에서는 시스템공학연구소 주관 국어 정보 베이스 개발 사업의 일환으로 고려대학교에서 구축 중인 오프라인 한글 글씨 영상 데이터베이스, KU-1에 대해 간략히 소개하고자 한다. 본 데이터베이스는 KS C 완성형 한글 사용 빈도순 상위 1,500자에 대하여 다양한 계층, 직업, 연령, 지역 분포를 고려한 1,000명 이상의 필기자가 정서체와 본인의 평소 자유 필체로 필기한 1,000벌의 명도 한글 글씨 영상으로 구성되어 있다.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.4
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• pp.113-130
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• 2003

Libraries manage e-Books as a new kinds of library materials and provide library users with information services in Korea. Initially, this study was intended to be an investigation into several misconceptions surrounding e-Books and their pricing structure. This study is also concerned with the fallacies of unifying e-Book techniques from four perspectives: (1)the misunderstandings related to unifying viewer and DRM, (2)the misconceptions about unifying service techniques in the industrial structure, (3)the analyses of essence of e-Book techniques, (4)the settlement of users´ inconveniences through continuous technique refinement. Based on the results, this study suggests various problems associated with the collaborative purchase of e-Books and presents several ideal strategies for their acquisition and services.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.1-7
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• 2021

Recently, since most of the research on correcting speech recognition errors is based on English, there is not enough research on Korean speech recognition. Compared to English speech recognition, however, Korean speech recognition has many errors due to the linguistic characteristics of Korean language, such as Korean Fortis and Korean Liaison, thus research on Korean speech recognition is needed. Furthermore, earlier works primarily focused on editorial distance algorithms and syllable restoration rules, making it difficult to correct the error types of Korean Fortis and Korean Liaison. In this paper, we propose a context-sensitive post-processing model of speech recognition using a LSTM-based sequence-to-sequence model and Bahdanau attention mechanism to correct Korean speech recognition errors caused by the pronunciation. Experiments showed that by using the model, the speech recognition performance was improved from 64% to 77% for Fortis, 74% to 90% for Liaison, and from 69% to 84% for average recognition than before. Based on the results, it seems possible to apply the proposed model to real-world applications based on speech recognition.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.233-240
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• 2019

In order to predict and respond to cyber attacks, a number of security companies quickly identify the methods, types and characteristics of attack techniques and are publishing Security Intelligence Reports(SIRs) on them. However, the SIRs distributed by each company are huge and unstructured. In this paper, we propose a framework that uses five analytic techniques to formulate a report and extract key information in order to reduce the time required to extract information on large unstructured SIRs efficiently. Since the SIRs data do not have the correct answer label, we propose four analysis techniques, Keyword Extraction, Topic Modeling, Summarization, and Document Similarity, through Unsupervised Learning. Finally, has built the data to extract threat information from SIRs, analysis applies to the Named Entity Recognition (NER) technology to recognize the words belonging to the IP, Domain/URL, Hash, Malware and determine if the word belongs to which type We propose a framework that applies a total of five analysis techniques, including technology.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.1-14
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• 2024

Objectives: The purpose of this study is to analyze the relationship between health information literacy and life satisfaction according to households type of the elderly targeting 9,820 people aged 65 or older using data from the 2021 Community Health Survey. Methods: This study used SPSS 27.0 to conduct logistic regression analysis to analyze the relationship between the study subjects' health literacy and life satisfaction. Results: Single-person households had higher life satisfaction when they perceived written health literacy to be easy to understand, and multi-person households had higher life satisfaction when they perceived health information explained verbally by medical staff to be easy to understand. Conclusions: There is a need to develop customized education programs and elderly health policies that take into account the characteristics of each households type.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.229-236
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• 2003

Named entity recognition is the process indispensable to question answering and information extraction systems. This paper presents an HMM based named entity (m) recognition method using the construction principles of compound words. In Korean, many named entities can be decomposed into more than one word. Moreover, there are contextual relationships among nouns in an NE, and among an NE and its surrounding words. In this paper, we classify words into a word as an NE in itself, a word in an NE, and/or a word adjacent to an n, and train an HMM based on NE-related word types and parts of speech. Proposed named entity recognition (NER) system uses trigram model of HMM for considering variable length of NEs. However, the trigram model of HMM has a serious data sparseness problem. In order to solve the problem, we use multi-level back-offs. Experimental results show that our NER system can achieve an F-measure of 87.6% in the economic articles.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.285-292
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• 2014

A named entity recognition method is used to improve the performance of information retrieval systems, question answering systems, machine translation systems and so on. The targets of the named entity recognition are usually PLOs (persons, locations and organizations). They are usually proper nouns or unregistered words, and traditional named entity recognizers use these characteristics to find out named entity candidates. The titles of books, movies and TV programs have different characteristics than PLO entities. They are sometimes multiple phrases, one sentence, or special characters. This makes it difficult to find the named entity candidates. In this paper we propose a method to quickly extract title named entities from news articles and automatically build a named entity dictionary for the titles. For the candidates identification, the word phrases enclosed with special symbols in a sentence are firstly extracted, and then verified by the SVM with using feature words and their distances. For the classification of the extracted title candidates, SVM is used with the mutual information of word contexts.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.07a
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• pp.138-141
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• 2003

스마트카드와 같은 장치의 부채널 공격이 가능한 것으로 입증되면서 많은 연구가 진행되고 있다. 부채널 공격의 일종인 오류기반 공격은 구현 가능성이 논란의 대상이었지만 카메라 플래쉬를 이용한 광학적 공격이 보고되면서 실현 가능성이 높은 것으로 인식되고 있다. 본 논문에서는 AES에 대해 향상된 오류기반 공격을 제안한다. 제안된 방법을 사용하면 공격에 필요한 암호문 수를 기존 방법보다 많이 줄일 수 있으며 최적의 조건에서는 하나의 암호문만으로 키를 얻을 수 있다. 오류는 일시적으로 생긴 후 없어지는 유형을 사용할 수도 있고 영구적인 것일 수도 있다. 오류에 의한 변경 확률이 1이 아닌 경우와 오류 발생 시점의 오차에 대해서도 살펴본다.