• 제목/요약/키워드: Keyword Learning

검색결과 196건 처리시간 0.023초

텍스트 마이닝을 통한 키워드 추출과 머신러닝 기반의 오픈소스 소프트웨어 주제 분류 (Keyword Extraction through Text Mining and Open Source Software Category Classification based on Machine Learning Algorithms)

  • 이예슬;백승찬;조용준;신동명
    • 한국소프트웨어감정평가학회 논문지
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    • 제14권2호
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    • pp.1-9
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    • 2018
  • 오픈소스를 사용하는 사용자 및 기업의 비중이 지속적으로 증가하고 있다. 국외뿐만 아니라 국내에서의 오픈소스 소프트웨어 시장 규모가 급격하게 성장하고 있다. 하지만 오픈소스 소프트웨어의 지속적인 발전에 비해서, 오픈소스 소프트웨어 주제 분류에 대한 연구 거의 이루어지지 않고 있으며 소프트웨어의 분류 체계 또한 구체화되어 있지 않다. 현재는 사용자가 주제를 직접 입력하거나 태깅하는 방식을 사용하고 있으며 이에 따른 오 분류 및 번거로움이 존재한다. 또한 오픈소스 소프트웨어 분류에 대한 연구는 오픈소스 소프트웨어 평가, 추천, 필터링등의 기반 연구로 이용될 수 있다. 따라서 본 연구에서는 머신러닝 모델을 사용하여 오픈소스 소프트웨어를 분류하는 기법에 대하여 제안하고, 머신러닝 모델 별 성능 비교를 제안한다.

가중치 기반 PLSA를 이용한 문서 평가 분석 (Reputation Analysis of Document Using Probabilistic Latent Semantic Analysis Based on Weighting Distinctions)

  • 조시원;이동욱
    • 전기학회논문지
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    • 제58권3호
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    • pp.632-638
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    • 2009
  • Probabilistic Latent Semantic Analysis has many applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. In this paper, we propose an algorithm using weighted Probabilistic Latent Semantic Analysis Model to find the contextual phrases and opinions from documents. The traditional keyword search is unable to find the semantic relations of phrases, Overcoming these obstacles requires the development of techniques for automatically classifying semantic relations of phrases. Through experiments, we show that the proposed algorithm works well to discover semantic relations of phrases and presents the semantic relations of phrases to the vector-space model. The proposed algorithm is able to perform a variety of analyses, including such as document classification, online reputation, and collaborative recommendation.

Analyzing the Effect of Lexical and Conceptual Information in Spam-mail Filtering System

  • Kang Sin-Jae;Kim Jong-Wan
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.105-109
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    • 2006
  • In this paper, we constructed a two-phase spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the ham (non-spam) mail. The definite information is the mail sender's information, URL, a certain spam keyword list, and the less definite information is the word list and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning in the 2nd phase. According to our results the ham misclassification rate was reduced if more lexical information was used as features, and the spam misclassification rate was reduced when the concept codes were included in features as well.

에이전트에 기반한 탈놀이 안내 시스템의 설계 및 구현 (Design and Implementation of an Agent-Based Guidance System for Mask Dances)

  • 강오한
    • 한국산업정보학회논문지
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    • 제7권2호
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    • pp.40-45
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    • 2002
  • 본 논문에서는 웹을 통하여 탈놀이에 관한 멀티미디어 정보를 제공하는 에이전트 기반의 탈놀이안내 시스템을 설계하고 구현한다. 사용자가 요구사항을 입력하면 클라이언트는 서버에게 이를 전송하고, 서버는 입력된 조건을 만족하는 탈놀이의 동영상 및 안내음성을 웹을 통하여 클라이언트에게 전송하여 상영한다. 본 논문에서는 에이전트 기반의 안내 시스템을 개발하기 위하여 인터페이스 에이전트, 사용자 모델링 에이전트, 중재 에이전트, 자료관리 에이전트를 설계하고 구현하였다. 또한 개발한 탈놀이 안내 시스템은 멀티미디어 데이터를 생성하는 기본기능 외에도 키워드를 이용한 검색 학습 등의 다양한 기능을 제공한다.

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Unicode 기반 다국어 명함인식기 개발 (A Development of Unicode-based Multi-lingual Namecard Recognizer)

  • 장동협;이재홍
    • 정보처리학회논문지B
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    • 제16B권2호
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    • pp.117-122
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    • 2009
  • 명함을 이용한 전세계적인 고객 관리 시스템을 구축하기 위해 다국어 명함인식기를 개발하였다. 먼저 다양한 언어의 문자인식 및 학습을 위해 Unicode 기반 문자 이미지 DB를 구축하였으며, 다양한 입력 장치를 통해 획득한 명함 영상에 대하여 정확한 데이터를 얻기 위한 다양한 컬러영상 처리 기술이 적용되었다. 다음에 다층 퍼셉트론 신경망, 언어 유형별 개별 문자인식, 각 언어별 명함에 사용된 필드별 키워드 DB를 이용한 후처리를 적용하여 명함 인식률을 향상시켰다.

The Influence of Factors Related to Preparation by Pre-Service Teachers for Gender Equity Education and Teaching Gender Equity

  • Kwon, Yoo-Jin;Jeon, Se-Kyung
    • International Journal of Human Ecology
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    • 제11권1호
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    • pp.97-107
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    • 2010
  • Gender equity education is ineffective in a public school system even though gender equity education is a current issue in South Korean education. One of the problems is attributed to teacher education because no better gender equity education can be accomplished without teacher preparation. Therefore, the effectiveness of teachers is a very important keyword in teacher education. This study examines learning experience, gender equity value, teacher preparation for gender equity education of pre-service teachers in Gonju, South Korea, the factors that influence teacher preparation for gender equity education, and the instruction of gender equity. A survey was delivered to pre-service teachers in 2008, and the data of 350 pre-service teachers were analyzed. MANOVA and Multiple Regressions were used for analyzing the data. The results will contribute to the development of effective teacher education for gender equity education and information on a partnership between the family and the public school system that is centered on gender equity education.

LEED 인증사례 분석을 통한 교육시설의 녹색건축 인증기준에 관한 연구 (A Study on Green Building Certification Criteria of Educational Facilities based on LEED Certified Cases)

  • 안동준
    • 한국태양에너지학회 논문집
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    • 제34권3호
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    • pp.122-132
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    • 2014
  • Sustainability became the keyword of our society worldwide, and it is undoubtful that buildings are mainly responsible for green house gas emission and energy consumption. Among different project types, educational facility was selected in this study to find out what needs to be addressed in order to provide students better learning environments. Scorecards from 32 LEED certified school projects went through analysis and essential components as design strategies in sustainable educational facilities were extracted based on application rate of each credit in LEED for School(2009). The extracted data were further analyzed in comparison with related components in G-SEED. The results would be used as guidelines for those of who design sustainable education facilities and prepare green building certifications. and it would further foster architect's responsibility towards green society in Korea.

Implementation of Extracting Specific Information by Sniffing Voice Packet in VoIP

  • Lee, Dong-Geon;Choi, WoongChul
    • International journal of advanced smart convergence
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    • 제9권4호
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    • pp.209-214
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    • 2020
  • VoIP technology has been widely used for exchanging voice or image data through IP networks. VoIP technology, often called Internet Telephony, sends and receives voice data over the RTP protocol during the session. However, there is an exposition risk in the voice data in VoIP using the RTP protocol, where the RTP protocol does not have a specification for encryption of the original data. We implement programs that can extract meaningful information from the user's dialogue. The meaningful information means the information that the program user wants to obtain. In order to do that, our implementation has two parts. One is the client part, which inputs the keyword of the information that the user wants to obtain, and the other is the server part, which sniffs and performs the speech recognition process. We use the Google Speech API from Google Cloud, which uses machine learning in the speech recognition process. Finally, we discuss the usability and the limitations of the implementation with the example.

2018년부터 2021년까지 대한안전경영과학회지의 주제어에 관한 분석 (An Analysis on Keywords in the Journal of Korean Safety Management Science from 2018 to 2021)

  • 양병학
    • 대한안전경영과학회지
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    • 제25권1호
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    • pp.1-6
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    • 2023
  • This study tried to analyze the keywords of the papers published in the Korea Safety Management Science by using the social network analysis. In order to extract the keywords, information on journal articles published from 2018 to 2021 was extracted from the SCIENCE ON. Among the keywords extracted from a total of 129 papers, the keywords with similar meanings were standardized. The keywords used in the same paper were visualized by connecting them through a network. Four centrality indicators of the social network analysis were used to analyze the effect of the keyword. Safety, Safety management, Apartment, Fire hose, SMEs, Virtual reality, Machine learning, Waterproof time, R&D capability, and Job crafting were selected as the keywords analyzed with high influence in the four centrality indicators.

앙상블 학습 알고리즘과 인공지능 표정 인식 기술을 활용한 사용자 감정 맞춤 힐링 서비스 (Using Ensemble Learning Algorithm and AI Facial Expression Recognition, Healing Service Tailored to User's Emotion)

  • 양성연;홍다혜;문재현
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2022년도 추계학술발표대회
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    • pp.818-820
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    • 2022
  • The keyword 'healing' is essential to the competitive society and culture of Koreans. In addition, as the time at home increases due to COVID-19, the demand for indoor healing services has increased. Therefore, this thesis analyzes the user's facial expression so that people can receive various 'customized' healing services indoors, and based on this, provides lighting, ASMR, video recommendation service, and facial expression recording service.The user's expression was analyzed by applying the ensemble algorithm to the expression prediction results of various CNN models after extracting only the face through object detection from the image taken by the user.