• Title/Summary/Keyword: Semantic Relationship

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Semantic Representation of Concept of Bio-signal Data (생체 신호 데이터의 의미 관계 표현)

  • Moon, Kyung-Sil;Park, Su-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.2
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    • pp.292-298
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    • 2011
  • In order to acquire new information and biological meaning of the signal data by defining the relationships between them, new modeling technique, ontology, has been proposed. The data of bio-signal can be represented as a systematic and logical to manage continuously bio-signal data using ontology. Furthermore, knowledge of which resources are utilized to provide improved service quality in medical information, health services in various fields. However, relevant studies have not been performed actively to compare importance of relationships between bio-signals. Therefore semantic representation of biometric information should be by defining the relationship between bio-signals. In this paper, we have developed bio-signal ontology to use as a model for using domain knowledge. We verified the usefulness of the ontology by using scenarios.

Extraction method of spatial relation by analyzing location tag in folksonomy (폭소노미에서 위치태그 분석을 통한 공간관계 추출 기법)

  • Choi, Yun-Hee;Yong, Hwan-Seung
    • Journal of Korea Multimedia Society
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    • v.12 no.8
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    • pp.1043-1054
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    • 2009
  • As the semantic web receives higher concern with an intensified necessity in these days, the research on the ontology as its core technology has been carried out in various fields. The ontology has been adopted as an alternative to work out lots of problematic issues resulted from the insufficient vocabulary selection rules in folksonomy, widely accepted under Web 2.0. Therefore the importance of research to complementarily consolidate the two disciplines, the folksonomy and the ontology, has been increased. Based on this idea this research proposes a system, which pulls out, using open services, the location information tags from folksonomy-based metadata, ultimately extracts, following location information analyses, spatial relationships among tags, and in turn automatically constructs self-correcting location information domain ontology. The system devised in this study will associate data derived from easily accessible folksonomy with meaningful and technological information from ontology.

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Consumer Perception of Types of Fashion Live Commerce: Using Text Mining (패션 라이브 커머스 유형별 소비자 인식 비교: 텍스트 마이닝 적용)

  • Gwak, Ha-Yeon;Lee, Kyu-Hye
    • Journal of Fashion Business
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    • v.25 no.3
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    • pp.90-107
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    • 2021
  • This study concludes that communication based on interaction between broadcasting hosts and consumers is differently characterized by fashion live commerce types. Subcategories of the types of fashion live commerce were created and used in the analyses of domestic consumer awareness. Three subcategories were created: The department store type, Designer brand type, and Influencer host type. Comments representing consumers' awareness that appear immediately during real-time broadcasting were collected and used for the analyses. The frequency and TF-IDF-based top keywords were selected to analyze the semantic network and CONCOR, and the top keywords were analyzed by deriving the values of degree of centrality. The analysis identified that a group of product attributes and a group of live commerce offered value were common between the three types. As for the group characteristics classified by type, for the department store types, brand attributes, benefits, and values from pursuing the products were identified. For designer brand types, a group of viewers' responses and inquiries were identified. It is interpreted that the satisfaction value gained from hosts with product expertise has been clustered. Influencer host types have affirmed a group of external product values. A close relationship is formed and it is thought to have led a group of values to trust the external image of the product. This study carries significance in analyzing real-time comment data from consumers using fashion live commerce to empirically reveal the characteristics of each type.

The Concessive Conjunctive Phrase todavía que in Some Areas of Latin America (라틴아메리카 일부 지역에서 사용되는 양보 접속사구 todavía que의 특성)

  • Kwak, Jae-Yong
    • Cross-Cultural Studies
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    • v.46
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    • pp.143-171
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    • 2017
  • In this paper, we present a morphosyntactic and semantic study of the concessive conjunctive phrase [todavía que] in the Andean and River Plate areas of Latin America. Real Academia $Espa{\tilde{n}}ola$(2009) describes that the adverb todavía occurs in a variety of focus-sensitive environments and specially, in the Andean and River Plate areas, the phrase [todavía que] participates in the concessive constructions and triggers an additive interpretation. It is well known that the Quechuan suffix '-raq' and the Aymaran suffix '-raki' have the meaning of todavía which is characterized as a additive particle. Due to the absence of the paratactic relationship between the mentioned Spanish adverb and those indigenous suffixes, the adverb todavía in [todavía que] is used as a additive focalizer. We assume that these morphosyntactic and semantic properties are derived from the language contact of Quechua-Spanish and Aymara Spanish. Based on this assumption, we will further assume that the etymological peculiarity of todavía as a universal quantifier is closely related to the reading of [todavía que] as a Scalar Additive Concessive Conjunctive Phrase.

Network Analysis between Uncertainty Words based on Word2Vec and WordNet (Word2Vec과 WordNet 기반 불확실성 단어 간의 네트워크 분석에 관한 연구)

  • Heo, Go Eun
    • Journal of the Korean Society for Library and Information Science
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    • v.53 no.3
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    • pp.247-271
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    • 2019
  • Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

Improving the effectiveness of document extraction summary based on the amount of sentence information (문장 정보량 기반 문서 추출 요약의 효과성 제고)

  • Kim, Eun Hee;Lim, Myung Jin;Shin, Ju Hyun
    • Smart Media Journal
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    • v.11 no.3
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    • pp.31-38
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    • 2022
  • In the document extraction summary study, various methods for selecting important sentences based on the relationship between sentences were proposed. In the Korean document summary using the summation similarity of sentences, the summation similarity of the sentences was regarded as the amount of sentence information, and the summary sentences were extracted by selecting important sentences based on this. However, the problem is that it does not take into account the various importance that each sentence contributes to the entire document. Therefore, in this study, we propose a document extraction summary method that provides a summary by selecting important sentences based on the amount of quantitative and semantic information in the sentence. As a result, the extracted sentence agreement was 58.56% and the ROUGE-L score was 34, which was superior to the method using only the combined similarity. Compared to the deep learning-based method, the extraction method is lighter, but the performance is similar. Through this, it was confirmed that the method of compressing information based on semantic similarity between sentences is an important approach in document extraction summary. In addition, based on the quickly extracted summary, the document generation summary step can be effectively performed.

Intellectual structure and research trends of The Research Journal of the Costume Culture - Bibliometric quantitative and qualitative semantic network approaches - (<복식문화연구>의 지적구조와 연구동향 - 계량정보학적 양적 접근과 의미연결망의 질적 접근 -)

  • Choi, Yeong-Hyeon;Choi, Mi-Hwa
    • The Research Journal of the Costume Culture
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    • v.30 no.4
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    • pp.608-630
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    • 2022
  • The purpose of this study is to examine the relationships between citations and the research trends of The Research Journal of the Costume Culture (RJCC) using bibliometric and network analyses. The results are as follows. First, the RJCC has been cited by a greater number of journals and high-reputation journals today. The RJCC has been mentioned in global academic journals in various fields, and it has been noted the most in environmental science. Second, because of examining the articles published in the RJCC over the past three years (2019 - 2021), it was found that the number of topics was evenly distributed in various subfields of the clothing and textiles sector. The RJCC principally deals with traditional clothing, ethics and sustainability, and technology, which means that the RJCC reflects the past, present, and future. As a result of conducting a cluster analysis using the Wakita-Tsurumi algorithm, the subjects of ethical fashion and sustainability were derived from the subdivisions of the RJCC. This suggests that the RJCC is a journal specialized in ethical fashion and sustainability sectors such as environmental, animal, and labor ethics. This study outlined the current status and future direction of academic journals in the field of clothing through an analysis of the RJCC's influence change and the relationship between citations. In addition, it is academically significant because it identifies research trends and knowledge-structure changes in the apparel science field by identifying changes in research keywords and significant research topics by sector.

A Study on the Development of Content Components in Information Literacy Textbooks: Focusing on the internal coherence of the learning contents (정보활용교육 관련 교과서류의 내용 요소 전개에 관한 연구 - 학습 내용의 내재적 통일성을 중심으로 -)

  • Byoung-Moon So
    • Journal of Korean Library and Information Science Society
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    • v.53 no.4
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    • pp.25-44
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    • 2022
  • The purpose of this study is to examine how the content components of information literacy textbooks develop and is to find implications for improving of textbook publication. Three kinds of information literacy textbooks were published sequentially over time. The content components of 『Information and media』(1996) and 『Library and information skills』(2011) are processed by filament structure and 『Information and library』(2002) has a topic-driven project activity. Generally, a small lesson unit of the textbook consisted of three components (learning goals, learning contents, learning activities) and each component in the unit have to make semantic close relationships. However, in some information literacy textbooks, there are cases that the semantic relationship between goals, contents, and activities are cut off. This disconnection cases can be a fatal drawback for the reliability of textbooks, so sufficient attention is needed to develop information literacy textbooks later.

BERT & Hierarchical Graph Convolution Neural Network based Emotion Analysis Model (BERT 및 계층 그래프 컨볼루션 신경망 기반 감성분석 모델)

  • Zhang, Junjun;Shin, Jongho;An, Suvin;Park, Taeyoung;Noh, Giseop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.34-36
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    • 2022
  • In the existing text sentiment analysis models, the entire text is usually directly modeled as a whole, and the hierarchical relationship between text contents is less considered. However, in the practice of sentiment analysis, many texts are mixed with multiple emotions. If the semantic modeling of the whole is directly performed, it may increase the difficulty of the sentiment analysis model to judge the sentiment, making the model difficult to apply to the classification of mixed-sentiment sentences. Therefore, this paper proposes a sentiment analysis model BHGCN that considers the text hierarchy. In this model, the output of hidden states of each layer of BERT is used as a node, and a directed connection is made between the upper and lower layers to construct a graph network with a semantic hierarchy. The model not only pays attention to layer-by-layer semantics, but also pays attention to hierarchical relationships. Suitable for handling mixed sentiment classification tasks. The comparative experimental results show that the BHGCN model exhibits obvious competitive advantages.

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Using Text Mining and Social Network Analysis to Identify Determinant Characteristics Affecting Consumers' Evaluation of Clothing Fit (텍스트 마이닝과 소셜 네트워크 분석 기법을 활용한 소비자의 의복 맞음새(Fit)평가에 영향을 미치는 특성)

  • Soo Hyun Hwang;Juyeon Park
    • Science of Emotion and Sensibility
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    • v.26 no.1
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    • pp.101-114
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    • 2023
  • This research aimed to recognize the determinant characteristics affecting consumers' clothing fit evaluation by employing text mining and social network analysis. For this aim, we first extracted text data linked to clothing fit from 2,000 consumer reviews collected from social network services and conducted semantic network examination and CONCOR analysis. As a result, we reported that "pants" and "skirts" were the most commonly associated clothing items with consumers' clothing fit evaluation. And the length of clothing was most commonly investigated. Then, the "waist" and "hip" were the most critical body parts affecting consumers' perception of clothing fit. Further, the four keywords including "wide," "large," "short," and "long" were the most employed ones in consumer reviews when evaluating clothing fit. This study is meaningful in that it specifically recognized the structural relationship and semantic meanings of keywords relevant to consumers' evaluation of clothing fit, which could bring empirical reference information for advanced clothing fit.