• 한국인터넷방송통신학회논문지
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• 제17권3호
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• pp.121-127
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• 2017

최근 공간 데이터와 같은 2차원 데이터를 위한 Semantic Web에 대한 연구가 활발하게 진행되고 있다. 2차원 Semantic Web은 기존의 Geospatial Web과 Semantic Web이 접목되어 다양한 지리 공간 정보와 일반 웹 상의 방대한 비공간 정보를 효율적으로 연계 및 통합하여 제공할 수 있는 지능적인 지리정보 웹 서비스 기술이다. 하지만 다차원 데이터 처리를 위한 연구는 전체적으로 부족한 편이며, 관련 표준 역시 제정되어 있지 않다. 따라서 본 논문에서는 그동안 진행되었던 Ontology 처리 기술과 관련된 다양한 기반 이론 및 기술들을 적용하여 다차원 데이터 처리가 가능한 온톨로지, 질의, 추론에 대한 내용을 제안하였다. 또한 각각 제안한 내용을 다차원 질의가 필요한 가상 시나리오에 적용해보았다.

• 한국IT서비스학회지
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• 제7권3호
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• pp.253-269
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• 2008

In this paper, we present an application called Semantic Search which is built on different supporting technologies and is designed to improve traditional web searching. The Semantic Search is becoming crucial challenges on semantic web. The assessment and the implementation of the research on Semantic Search is not full-fledged whereas its research is highly interested. Also there exists only little research that offers a commercial use Semantic Search System that should be taken into the account in measuring the effectiveness of a Semantic Search System. This paper proposes an implementation and evaluation for the Semantic Search System. Firstly, we built Semantic Search System which includes a case of development and it's procedure. Secondly, We presented the measurement of our Semantic Search System's effectiveness. Finally, the evaluation offers useful implications to the researchers and practitioners to improve the research level to the commercial use.

• 산업기술연구
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• 제25권A호
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• pp.123-131
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• 2005

Semantic object model has widely been recognized as an alternative data modeling approach to entity-relationship model for database system design. In this study, we have presented a semantic object model for intermediary type shopping mall consisting of multiple buyers and sellers. Essential processes and information with regard to the customer management, product management, price estimation, product order etc. have been considered for this study. Upon careful examination and analysis of them, a detailed semantic objects and attributes have been drawn and structured into semantic object diagrams. The final objects were converted into an entity-relationship diagram so that intuitive comparison could be made for relational database design. The results in this study may form a conceptual framework for both academic concerns and more complicated system applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• International Journal of Knowledge Content Development & Technology
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• 제4권1호
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• pp.39-51
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• 2014

The paper proposes that the Basic Concepts Classification (BCC) could serve as the controlled vocabulary for the Semantic Web. The BCC uses a synthetic approach among classes of things, relators, and properties. These are precisely the sort of concepts required by RDF triples. The BCC also addresses some of the syntactic needs of the Semantic Web. Others could be added to the BCC in a bottom-up process that carefully evaluates the costs, benefits, and best format for each rule considered.

• Journal of information and communication convergence engineering
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• 제22권1호
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• pp.33-43
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• 2024

Automated text summarization (ATS) systems rely on language resources as datasets. However, creating these datasets is a complex and labor-intensive task requiring linguists to extensively annotate the data. Consequently, certain public datasets for ATS, particularly in languages such as Thai, are not as readily available as those for the more popular languages. The primary objective of the ATS approach is to condense large volumes of text into shorter summaries, thereby reducing the time required to extract information from extensive textual data. Owing to the challenges involved in preparing language resources, publicly accessible datasets for Thai ATS are relatively scarce compared to those for widely used languages. The goal is to produce concise summaries and accelerate the information extraction process using vast amounts of textual input. This study introduced ThEconSum, an ATS architecture specifically designed for Thai language, using economy-related data. An evaluation of this research revealed the significant remaining tasks and limitations of the Thai language.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4476-4490
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• 2017

The aim of image annotation is to determine labels that can accurately describe the semantic information of images. Many approaches have been proposed to automate the image annotation task while achieving good performance. However, in most cases, the semantic similarities of images are ignored. Towards this end, we propose a novel Visual-Semantic Nearest Neighbor (VS-KNN) method by collectively exploring visual and semantic similarities for image annotation. First, for each label, visual nearest neighbors of a given test image are constructed from training images associated with this label. Second, each neighboring subset is determined by mining the semantic similarity and the visual similarity. Finally, the relevance between the images and labels is determined based on maximum a posteriori estimation. Extensive experiments were conducted using three widely used image datasets. The experimental results show the effectiveness of the proposed method in comparison with state-of-the-arts methods.

• 한국항행학회논문지
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• 제12권4호
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• pp.372-377
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• 2008

본 논문은 의미특징행렬(semantic feature matrix)과 의미변수행령(semantic variable matrix)을 이용하는 질의 기반의 새로운 문서를 요약방법을 제안한다. 제안된 방법은 비지도 학습 방법으로 질의와 문장 간에 사전학습이 필요 없고, 의미 특징(semantic feature)과 의미변수(semantic variable)를 이용하여 질의에 적합한 하위 주제를 잘 반영하여서 정확한 문서를 요약 할 수 있다. 이것은 비음수 행렬 분해가 주제들로 구성된 문서의 내부구조를 나타내는 의미특징을 자연스럽게 추출할 수 있기 때문이다. 실험결과 제안방법이 다른 방법에 비하여 좋은 성능을 보인다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 춘계학술발표논문집 (상)
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• pp.713-716
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• 2003

Semantic Web 환경을 구축하고, Semantic Web 환경에서 자동화된 서비스 발견, 서비스 수행, 서비스 구성과 상호운영이라는 Semantic web service를 수행할 수 있는 DAML-based web service 온톨로지를 이용하여 자동화된 항공권 예약 서비스와 테마별 여행 스케줄 서비스를 제공하는 프로토타이프 테스트 베드 구축에 대해 살펴 볼 것이다.