• Title/Summary/Keyword: Semantic relationships

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Arab Spring Effects on Meanings for Islamist Web Terms and on Web Hyperlink Networks among Muslim-Majority Nations: A Naturalistic Field Experiment

  • Danowski, James A.;Park, Han Woo
    • Journal of Contemporary Eastern Asia
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    • v.13 no.2
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    • pp.15-39
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    • 2014
  • This research conducted a before/after naturalistic field experiment, with the early Arab Spring as the treatment. Compared to before the early Arab Spring, after the observation period the associations became stronger among the Web terms: 'Jihad, Sharia, innovation, democracy and civil society.' The Western concept of civil society transformed into a central Islamist ideological component. At another level, the inter-nation network based on Jihad-weighted Web hyperlinks between pairs of 46 Muslim Majority (MM) nations found Iran in one of the top two positions of flow betweenness centrality, a measure of network power, both before and after early Arab Spring. In contrast, Somalia, UAE, Egypt, Libya, and Sudan increased most in network flow betweenness centrality. The MM 'Jihad'-centric word co-occurrence network more than tripled in size, and the semantic structure more became entropic. This media "cloud" perhaps billowed as Islamist groups changed their material-level relationships and the corresponding media representations of Jihad among them changed after early Arab Spring. Future research could investigate various rival explanations for this naturalistic field experiment's findings.

Using Spatial Ontology in the Semantic Integration of Multimodal Object Manipulation in Virtual Reality

  • Irawati, Sylvia;Calderon, Daniela;Ko, Hee-Dong
    • Journal of the HCI Society of Korea
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    • v.1 no.1
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    • pp.9-20
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    • 2006
  • This paper describes a framework for multimodal object manipulation in virtual environments. The gist of the proposed framework is the semantic integration of multimodal input using spatial ontology and user context to integrate the interpretation results from the inputs into a single one. The spatial ontology, describing the spatial relationships between objects, is used together with the current user context to solve ambiguities coming from the user's commands. These commands are used to reposition the objects in the virtual environments. We discuss how the spatial ontology is defined and used to assist the user to perform object placements in the virtual environment as it will be in the real world.

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A Study on Ontology Generation by Machine Learning in Big Data (빅 데이터에서 기계학습을 통한 온톨로지 생성에 관한 연구)

  • Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.645-646
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    • 2018
  • Recently, the concept of machine learning has been introduced as a decision making method through data processing. Machine learning uses the results of running based on existing data as a means of decision making. The data generated by the development of technology is vast. This data is called big data. It is important to extract the necessary data from these data. In this paper, we propose a method for extracting related data for constructing an ontology through machine learning. The results of machine learning can be given a relationship from a semantic perspective. it can be added to the ontology to support relationships depending on the needs of the application.

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Text Mining Analysis of the Online Counseling Contents of Nursery School Teachers (텍스트 마이닝을 활용한 어린이집교사 온라인 상담의 내용분석)

  • Jeon, Ji Won;Lim, Sun Ah;Jung, Yunhee
    • Korean Journal of Childcare and Education
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    • v.16 no.6
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    • pp.253-272
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    • 2020
  • Objective: This study aimed to analyze the counseling contents of daycare center teachers by using text mining and semantic network analysis methods to find the necessary support directions for daycare teachers and to improve the quality of child-care. Methods: Five hundred thirteen cases of counseling recorded on the open bulletin board of online counseling (Naver Bands for Nursery Teacher Counseling) were collected, and frequency analysis, centrality solidarity analysis, and machine learning-based topic analysis were conducted using the NetMiner4.3 program. Results: First, 'teacher-to-child ratio' was highest in the frequency. Second, 'colleagues' were all high in all centrality analysis. Third, machine learning-based topical analysis shows that the topics were categorized as subjects about 'childcare and education', 'working environment that supports professional development' and 'working condition', and among them, 'first-time teacher concerns' accounted for 44% of the total counseling content. Conclusion/Implications: This study implied that it is necessary to provide high-quality child-care and education to infants by lowering the 'teacher-to-child ratio', and a systematic program is needed to help improve effective communication skills in interpersonal relationships such as between parents, fellow teachers, and principals. In addition, self-development and efforts to improve teachers expertise should be prioritized in order to improve infant care quality and quality of teachers.

Survey of Automatic Query Expansion for Arabic Text Retrieval

  • Farhan, Yasir Hadi;Noah, Shahrul Azman Mohd;Mohd, Masnizah
    • Journal of Information Science Theory and Practice
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    • v.8 no.4
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    • pp.67-86
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    • 2020
  • Information need has been one of the main motivations for a person using a search engine. Queries can represent very different information needs. Ironically, a query can be a poor representation of the information need because the user can find it difficult to express the information need. Query Expansion (QE) is being popularly used to address this limitation. While QE can be considered as a language-independent technique, recent findings have shown that in certain cases, language plays an important role. Arabic is a language with a particularly large vocabulary rich in words with synonymous shades of meaning and has high morphological complexity. This paper, therefore, provides a review on QE for Arabic information retrieval, the intention being to identify the recent state-of-the-art of this burgeoning area. In this review, we primarily discuss statistical QE approaches that include document analysis, search, browse log analyses, and web knowledge analyses, in addition to the semantic QE approaches, which use semantic knowledge structures to extract meaningful word relationships. Finally, our conclusion is that QE regarding the Arabic language is subjected to additional investigation and research due to the intricate nature of this language.

A Study to Rethink the Components of Teaching Korean Genitive Particle '의': Based on the Errors in Korean Learners' Corpus (한국어 학습자 대상 관형격 조사 '의'의 교육 내용 재고: 학습자 말뭉치에 나타난 오류를 바탕으로)

  • Soo-Hyun Lee;Ji-Young Sim
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.3
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    • pp.443-454
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    • 2023
  • The purpose of this study is to reveal the Korean learners' usage pattern of '의', the genitive particle, according to semantic classification, so that it can be referred to in determining the contents and methods of related education. The method of this study adopts a quantitative analysis using learners corpus established by National Institute of Korean Language. As a result of the analysis, as proficiency increases, the overall frequency of '의' increases and the number of meaning senses used increases. However, the frequency of errors also increases with it. As for the usage pattern of each sense, the meaning of 'ownership, belonging' is the most frequent, and followed by 'acting entity', 'kinship, social relations', and 'relationship(area)'. In conclusion, the meanings of 'acting subjects' and 'relationships(area) need to be supplemented with explicit education. Other meanings need to be discussed, and decisions should be made in consideration of learning purpose and proficiency.

A Model for Ranking Semantic Associations in a Social Network (소셜 네트워크에서 관계 랭킹 모델)

  • Oh, Sunju
    • The Journal of Society for e-Business Studies
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    • v.18 no.3
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    • pp.93-105
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    • 2013
  • Much Interest has focused on social network services such as Facebook and Twitter. Previous research conducted on social network often emphasized the architecture of the social network that is the existence of path between any objects on network and the centrality of the object in the network. However, studies on the semantic association in the network are rare. Studies on searching semantic associations between entities are necessary for future business enhancements. In this research, the ontology based social network analysis is performed. A new method to search and rank relation sequences that consist of several relations between entities is proposed. In addition, several heuristics to measure the strength of the relation sequences are proposed. To evaluate the proposed method, an experiment was performed. A group of social relationships among the university and organizations are constructed. Some social connections are searched using the proposed ranking method. The proposed method is expected to be used to search the association among entities in ontology based knowledge base.

An Efficient Query Rewriting Technique Utilizing Semantic Information and Materialized Views (의미 정보와 실체뷰를 활용한 효율적 질의 재구성 기법)

  • Chang, Jae-Young
    • The KIPS Transactions:PartD
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    • v.10D no.4
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    • pp.661-670
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    • 2003
  • Materialized views which are stored views of the database offer opportunities for significant performance gain in query valuation by providing fast access to pre-computed data. The question of when and how to use a materialized view in processing a given query is a difficult one attracting a significant amount of research. Whether a materialized view can be used in answering a query depends on the relationship between the view and the query. Proposed in this paper are new ways of utilizing materialized views in answering a query. Semantic relationships are used in addition to syntactic ones. We also utilize a materialized view in answering a query even if it has relations unrelated to the query. We first show the conditions for testing whether a materialized view can be utilized in answering a query and then present the algorithms for testing the conditions and reformulating a query with a materialized view.

The Development of Automatic Ontology Generation System Using Extended Search Keywords (검색 키워드 확장을 이용한 온톨로지 자동 생성 시스템 개발)

  • Shim, Joon;Lee, Hong-Chul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.6
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    • pp.1220-1228
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    • 2009
  • Ontologies, which are the core of the Semantic Web, are usually limited by specific domains or created by defining meanings and relationships that depend on the heuristic. However, the creation of an ontology is not only very difficult but also very time-consuming. In contrast with ontologies that are used in specific fields, an ontology for the Web entails an unlimited scope of knowledge and expression of information. Hence, it is hard to express information in the same way that is used to create ontologies in specific fields. Therefore, the automatic generation of an ontology takes very important role in the Semantic Web. In this paper, to make ontologies automatically, we suggest the methods to create and renew ontologies by expanding keywords related to the index-terms which are extracted from the search keywords which users input in the search engines by analyzing the morphemes.

Semi Automatic Ontology Generation about XML Documents

  • Gu Mi Sug;Hwang Jeong Hee;Ryu Keun Ho;Jung Doo Yeong;Lee Keum Woo
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.730-733
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    • 2004
  • Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

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