• 제목/요약/키워드: Semantic Generation

검색결과 203건 처리시간 0.022초

Semantic-based Query Generation For Information Retrieval

  • Shin Seung-Eun;Seo Young-Hoon
    • International Journal of Contents
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    • 제1권2호
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    • pp.39-43
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    • 2005
  • In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

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Handling Semantic Ambiguity for Metadata Generation

  • Yang, Gi-Chul;Park, Jeong-Ran
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권2호
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    • pp.1-6
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    • 2018
  • The following research questions are examined in this paper. What hinders quality metadata generation and metadata interoperability? What kind of semantic representation technique can be utilized in order to enhance metadata quality and semantic interoperability? This paper suggests a way of handling semantic ambiguity for metadata generation. The conceptual graph is utilized to disambiguate semantic ambiguities caused by isolation of a metadata element and its corresponding definition from the relevant context. The mechanism introduced in this paper has the potential to alleviate issues dealing with inconsistent metadata application and interoperability across digital collections.

Automatic Extraction of Metadata Information for Library Collections

  • Yang, Gi-Chul;Park, Jeong-Ran
    • International Journal of Advanced Culture Technology
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    • 제6권2호
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    • pp.117-122
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    • 2018
  • As evidenced through rapidly growing digital repositories and web resources, automatic metadata generation is becoming ever more critical, especially considering the costly and complex operation of manual metadata creation. Also, automatic metadata generation is apt to consistent metadata application. In this sense, metadata quality and interoperability can be enhanced by utilizing a mechanism for automatic metadata generation. In this article, a mechanism of automatic metadata extraction called ExMETA is introduced in order to alleviate issues dealing with inconsistent metadata application and semantic interoperability across ever-growing digital collections. Conceptual graph, one of formal languages that represent the meanings of natural language sentences, is utilized for ExMETA as a mediation mechanism that enhances the metadata quality by disambiguating semantic ambiguities caused by isolation of a metadata element and its corresponding definition from the relevant context. Hence, automatic metadata generation by using ExMETA can be a good way of enhancing metadata quality and semantic interoperability.

Video Captioning with Visual and Semantic Features

  • Lee, Sujin;Kim, Incheol
    • Journal of Information Processing Systems
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    • 제14권6호
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    • pp.1318-1330
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    • 2018
  • Video captioning refers to the process of extracting features from a video and generating video captions using the extracted features. This paper introduces a deep neural network model and its learning method for effective video captioning. In this study, visual features as well as semantic features, which effectively express the video, are also used. The visual features of the video are extracted using convolutional neural networks, such as C3D and ResNet, while the semantic features are extracted using a semantic feature extraction network proposed in this paper. Further, an attention-based caption generation network is proposed for effective generation of video captions using the extracted features. The performance and effectiveness of the proposed model is verified through various experiments using two large-scale video benchmarks such as the Microsoft Video Description (MSVD) and the Microsoft Research Video-To-Text (MSR-VTT).

CBD에 의한 온톨로지 기반 시맨틱 웹 서비스 생성 (Generation of semantic Web service based on Ontology by CBD)

  • 하얀
    • 정보처리학회논문지D
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    • 제14D권4호
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    • pp.389-394
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    • 2007
  • 본 연구는 자바와 C++ 컴포넌트로부터 동적으로 웹 서비스를 생성하기 위한 연구로써, 온톨로지를 이용하여 시맨틱 웹 서비스를 지원하고자 한다. 시맨틱 웹 서비스는 웹의 내용뿐 만 아니라 웹 서비스의 접근을 용이하게 하는 장점이 있다. 이를 위해 컴포넌트를 위한 시맨틱 서비스 발견이 필요하며, 컴포넌트로부터 웹서비스를 생성하기 위해 온톨로지 기반 프레임워크를 활용한다. 특히, 본 연구에서는 컴포넌트와 온톨로지를 UML 모델로 변환시키고, 이를 다시 WSDL 문서로 사상시키므로써, 객체 모델링를 이용한 동적 웹 서비스 생성을 한다. 본 연구의 주요 의의는 컴포넌트로부터 웹서비스를 동적으로 생성하는 것과 온톨로지를 사용하므로써, 시맨틱 웹 환경을 제공하는 것이다. 다시 말해, 본 연구 는 온톨로지 기반 시맨틱 웹 서비스와 CBD 방법론을 통합하고자 한다.

Deep Hashing for Semi-supervised Content Based Image Retrieval

  • Bashir, Muhammad Khawar;Saleem, Yasir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3790-3803
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    • 2018
  • Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

시맨틱 라이브러리를 위한 아키텍처 참조 모델 (Architectural Reference Model for Semantic Library)

  • 한성국;이현실
    • 정보관리학회지
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    • 제24권1호
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    • pp.75-101
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    • 2007
  • 기술 환경의 변화는 문헌정보시스템의 혁신적인 변화를 촉진하고 있다. 본 연구에서는 문헌 정보 체계기술과 인터넷 정보기술을 융합된 차세대 문헌 정보 시스템의 원형으로 시맨틱 라이브러리를 정의하고, 시맨틱 라이브러리의 기능적 요구사항과 아키텍처의 참조모델을 제시하였다. 시맨틱 라이브러리는 온톨로지와 메타데이터 기반의 의미적 상호 운용성과 통합을 실현하고 정보 자원의 개방과 공유 참여와 협업을 통하여 이용자 정보서비스를 혁신하는 체제이다. 또한 시맨틱 라이브러리는 FRBR의 논리구조를 근간으로 하여 서비스 지향 아키텍처로 구현됨으로써 효과적으로 시스템을 구축을 실현할 수 있다. 본 연구에서는 차세대 문헌정보 시스템의 모델로 6개 수평 계층과 3개 수직요소로 구성되는 시맨틱 라이브러리의 참조 모델을 제시하였다.

Deep learning approach to generate 3D civil infrastructure models using drone images

  • Kwon, Ji-Hye;Khudoyarov, Shekhroz;Kim, Namgyu;Heo, Jun-Haeng
    • Smart Structures and Systems
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    • 제30권5호
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    • pp.501-511
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    • 2022
  • Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

차세대 웹에서 온톨로지 기술을 통한 지식체계 적용 (Application of knowledge system through Ontology Technology in Next Generation Web)

  • 김민철
    • 기술혁신학회지
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    • 제8권2호
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    • pp.605-622
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    • 2005
  • Because, next generation web, semantic web consists of documents with semantic information, it enables computer interpret the contents of the documents, so that the information retrieval, interpretation and integration can be automated. The web documents with the semantic information may be made in ontology. In this paper, collaborative approach among the ontology design techniques is more excellent than the other techniques because it design the ontology through continuous evaluations and modification in terms of multiple views. So, we propose the process of designing and implementing the ontology for specific domain, which is Yeomigi tour place. Delphi technique, that is a kind of collaborative approach, is used when the ontology is designed.

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시멘틱 웹 기반 개방형 전자도서관 모델에 관한 연구 (A Study of Semantic Web Based Open Digital Library Model)

  • 황상규
    • 정보관리학회지
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    • 제21권1호
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    • pp.187-207
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    • 2004
  • 최근에 이르러 차세대 웹 아키텍처인 시멘틱 웹에 관한 연구에 대한 관심이 증대되고 있다. 정보학적인 관점에서, 차세대 웹 아키텍처인 시멘틱 웹은 하나의 거대한 메타데이터 조직으로 볼 수 있다 시멘틱 웹을 거대한 메타데이터 조직으로 볼 수 있는 가장 큰 이유는, 시멘틱 웹을 구축 과정에서 가장 중요한 단계 중 하나가 웹 정보자원에 대한 정형화된 메타데이터를 작성하는 것이기 때문이며, 이용자는 메타데이터를 이용하여 보다 쉽게 자신이 원하는 정보를 찾을 수 있다. 본 논문에서는, 시멘틱 웹 환경 하에서 서로 다른 정보체계구조를 지닌 개방형 전자도서관간의 상호 운영성을 제공하기 위하여 새로운 방식의 응용프로화일 메타데이터구조를 개발하였다. 새로운 방식의 응용프로화일 메타데이터구조를 토대로, 개방형도서관모델에서 서로 다른 형태의 대규모메타데이터를 통합하기 위한 통합메타데이터 자동생성 및 통합검색 알고리즘을 개발하였다.