• Title/Summary/Keyword: Semantic Net

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A Study on Field Compost Detection by Using Unmanned AerialVehicle Image and Semantic Segmentation Technique based Deep Learning (무인항공기 영상과 딥러닝 기반의 의미론적 분할 기법을 활용한 야적퇴비 탐지 연구)

  • Kim, Na-Kyeong;Park, Mi-So;Jeong, Min-Ji;Hwang, Do-Hyun;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.367-378
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    • 2021
  • Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

Knowledge-Based Web Document Filtering (지식기반 웹 문서 필터링)

  • 황상규;김상모;변영태
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.51-53
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    • 1999
  • 인터넷에서 검색 가능한 정보의 양은 폭발적으로 증가하고 있으며, 그에 따라 웹 기반 정보검색시스템은 사용자가 원하는 정보만을 필터링하여 이용자의 정보검색 수행과정에 부담을 덜어줄 필요가 있다. 본 연구에서는 웹 정보검색에 익숙치 못한 초보 이용자들이 실제 웹 정보검색을 수행하는데 있어 발생할 수 있는 문제점을 살펴보고, 초보 이용자들의 보다 편리한 웹 정보검색을 도와줄 수 있도록 하기 위하여 WordNet을 활용한 지식베이스와 SDCC(Semantic Distance for Common Category)를 이용한 웹 문서 필터링 알고리즘을 개발하고 그 효율성을 확인하였다.

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Refinement of KorLex based on WordNet (워드넷 기반 한국어 명사 어휘의미망의 정제)

  • Hwang, Soon-Hee;Yoon, Ae-Sun
    • Proceedings of the Korean Society for Cognitive Science Conference
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    • 2005.05a
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    • pp.267-272
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    • 2005
  • 최근 들어 온톨로지(ontology), 시소러스(thesaurus) 등과 함께 주목받고 있는 Princeton 대학의 워드넷(WordNet, 이하 PWN) 은 자연어 처리(NLP)와 관련하여 대안을 제시할 수 있는 어휘의미망(lexico-semantic network)이다. 또한 PWN을 기반으로 상이한 개별어 어휘의미망 구축이 여러 차례 시도되었고, 현재도 진행 중이다. 본 연구는 간접 구축 방식에 의한 어휘의미망 구축 시 요구되는 정제(refinement) 방식들을 검토하고, 이를 한국어 명사 어휘의미망(KL)에 적용하여 정확도 검증 방법의 한 대안으로 제시하였다. 또한 보다 정교한 정제 방법의 모색과 고찰은 향후 과제로 삼고자 한다.

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A Web Text Mining Technique using Semantic Relations based on WordNet and Text Corpus (WordNet과 텍스트 코퍼스에 기반한 의미 관계를 활용한 웹 텍스트 조사 기법)

  • Lee, Ho-Suk;Kim, Yung-Taek
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06c
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    • pp.181-184
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    • 2007
  • 본 논문은 문장 분석에 의하여 의미 관계를 생성하고 의미 네트워크에 의하여 유사한 의미 관계를 고려하는 의미 중심의 웹 텍스트 검색 기법에 대하여 논의한다. 기존의 웹 텍스트 검색은 단어만을 혹은 의미 관계만을 고려한 검색이었다고 할 수 있다. 그러나 문장 분석에 의한 의미 관계의 생성과 의미 네트워크에 의한 유사한 의미 관계의 고려는 기존의 단어 중심 혹은 의미 관계 중심의 검색 한계를 넘어서 유사한 의미 관계를 고려한 좀 더 포괄적이고 계층적인 검색을 가능하게 할 것으로 생각된다.

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Design and Implementation of lava ATM API (자바 ATM API의 설계 및 구현)

  • 성종진;이근구;김장경
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1998.11a
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    • pp.456-462
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    • 1998
  • 이 논문에서는 자바 환경에서 사용될 수 있는 ATM API를 정의하고, 이렇게 정의된 자바 ATM API를 Winsock 2 환경 상에서 구축할 경우 요구되는 소프트웨어의 구조와 구현 방법을 제시한다. 제안된 자바 ATM API는 기존의 자바 프로그래밍 환경에서 제공되는 JDK 중에서 인터넷 통신 기능을 정의하고 있는 java.net 패키지의 확장된 형태로 정의되었다. 동시에 순수 ATM 서비스의 표준인 ATM 포럼의 "Native ATM Services: Semantic Description, Version 1.0" 규격에 따른 표준화된 ATM 서비스 기능들을 제공할 수 있도록 정의되었다. 표준화된 ATM 서비스 제공을 위해 java.net에 추가적으로 정의된 자바ㆍATM API 용 클래스로는, ATM 어드레싱을 위한 AtmAddress, BLLI/BHLI 정보의 이용을 위한 AtmBLLI와 AtmBHLI, 소켓 개념의 통신 프로그래밍을 위한 AtmSocket, AtmServerSocket, AtmMulticastSocket, AtmSocketImpl 그리고 ATM 통신의 장점인 연결의 특성 표현을 위한 AtmConnAttr 등이다.

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An Analysis of Scientific Concepts Pre-service Elementary School Teachers Have through Semantic Network Analysis (의미 네트워크 분석법을 활용한 초등 예비교사들이 생각하는 과학에 대한 의미 분석)

  • Kim, Dong-Ryeul
    • Journal of Korean Elementary Science Education
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    • v.32 no.3
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    • pp.327-345
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    • 2013
  • This study aims to investigate how pre-service elementary school teachers understand 'something scientific', 'being scientific', 'scientific events' and 'scientific questions' through semantic network analysis. To achieve this purpose, this study carried out a central analysis of the frequency and density of words and the degree of connection between key words, a concentric analysis, a click analysis and a common network analysis through text semantic network analysis by using NetMiner 4.0 Program. Based on the results of these analyses, this study came to the following conclusions. Firstly, in perceiving 'something scientific', pre-service elementary school teachers recognized 'verification', 'objective' and 'experiment' as most important words. In other words, they perceived that main grounds for something scientific should be provided through clear facts, possible to be verified and accompanied by an exact and logical theoretical system. In regard to 'being scientific', they perceived 'explanation', 'objective' and 'verification' as most important words, while having a traditional point of view that science is a set that can be explained objectively. Secondly, in regard that the term, 'observation', is contained in 'scientific events', they showed a high rate of understanding it as a scientific event. In regard to scientifical reasons, they showed the highest frequency of 'observation', and for unscientific reasons, they showed the highest frequency of 'behavior'. In perceiving 'scientific questions', they showed the highest frequency of determining bacteria-related questions as scientific. As a reason why they thought as scientific, they mentioned 'observation' most frequently like 'scientific events', while mentioning 'value judgement' as a reason why they thought as unscientific most frequently. From the results of integrated network analysis, this study found out that words pre-service teachers commonly used in stating scientific events or scientific questions were overlapped with words they mentioned for scientific events or scientific questions. As a result, it was found there were many pre-service teachers having interpreted scientific words without clearly distinguishing scientific events or scientific questions.

The Structure of Healing in the Functor and Semantic Arguments Appearing in the Poem "Bellflower Flower" by Cho Ji-Hoon (조지훈의 시 「도라지꽃」에 나타나는 함수자와 의미론적 논항의 치유의 구조)

  • Park, In-kwa
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.1
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    • pp.275-278
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    • 2018
  • This study examines how poem and poetic ego of Cho Ji-Hoon form synapses. It is to clarify the synaptic structure of the healing, the contact point between the literary mechanism and the mechanism of the ego. Therefore, it aims to encode the active therapy by substituting the structure into the literary therapy program. Cho Ji-Hoon's poem "Bellflower Flower" is a mesh of poem, and a mesh of semantic arguments is set up for the 'Bellflower Flower' of functor. At this time, the longing that attracts depression to the net of the semantic argument is caught. This exists as a function of healing. If we embody a literary therapy program that utilizes the synaptic structure of this healing, it will be able to experience the function of literary therapy improved than before.

A Study on the Meaning of The First Slam Dunk Based on Text Mining and Semantic Network Analysis

  • Kyung-Won Byun
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.164-172
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    • 2023
  • In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

Construction of Variable Pattern Net for Korean Sentence Understanding and Its Application (한국어 문장이해를 위한 가변패턴네트의 구성과 응용)

  • Han, Gwang-Rok
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.2
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    • pp.229-236
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    • 1995
  • The conceptual world of sentence is composed f substantives(nouns) and verbal. The verbal is a semantic center of sentence, the substantives are placed under control of verbal, and they are combined in a various way. In this paper, the structural relation of verbal and substantives are analyzed and the phrase unit sentence which is derived from the result of morphological analysis is interpreted by a variable pattern net. This variable pattern net analyzes the phrases syntactically and semantically and extracts conceptual units of clausal form. This paper expands the traditionally restricted Horn clause theory to the general sentence, separates a simple sentence from a complex sentence automatically, constructs knowledge base by clausal form of logical conceptual units, and applies it to a question-answering system.

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A Framework for WordNet-based Word Sense Disambiguation (워드넷 기반의 단어 중의성 해소 프레임워크)

  • Ren, Chulan;Cho, Sehyeong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.4
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    • pp.325-331
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    • 2013
  • This paper a framework and method for resolving word sense disambiguation and present the results. In this work, WordNet is used for two different purposes: one as a dictionary and the other as an ontology, containing the hierarchical structure, representing hypernym-hyponym relations. The advantage of this approach is twofold. First, it provides a very simple method that is easily implemented. Second, we do not suffer from the lack of large corpus data which would have been necessary in a statistical method. In the future this can be extended to incorporate other relations, such as synonyms, meronyms, and antonyms.