• Title/Summary/Keyword: Semantic Expansion

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Linkage Expansion in Linked Open Data Cloud using Link Policy (연결정책을 이용한 개방형 연결 데이터 클라우드에서의 연결성 확충)

  • Kim, Kwangmin;Sohn, Yonglak
    • Journal of KIISE
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    • v.44 no.10
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    • pp.1045-1061
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    • 2017
  • This paper suggests a method to expand linkages in a Linked Open Data(LOD) cloud that is a practical consequence of a semantic web. LOD cloud, contrary to the first expectation, has not been used actively because of the lack of linkages. Current method for establishing links by applying to explicit links and attaching the links to LODs have restrictions on reflecting target LODs' changes in a timely manner and maintaining them periodically. Instead of attaching them, this paper suggests that each LOD should prepare a link policy and publish it together with the LOD. The link policy specifies target LODs, predicate pairs, and similarity degrees to decide on the establishment of links. We have implemented a system that performs in-depth searching through LODs using their link policies. We have published APIs of the system to Github. Results of the experiment on the in-depth searching system with similarity degrees of 1.0 ~ 0.8 and depth level of 4 provides searching results that include 91% ~ 98% of the trustworthy links and about 170% of triples expanded.

Ontology - Based Intelligent Rule Components Extraction (온톨로지 기반 지능형 규칙 구성요소 추출에 관한 연구)

  • Kim U-Ju;Chae Sang-Yong;Park Sang-Eon
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2006.06a
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    • pp.237-244
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    • 2006
  • 시맨틱 웹 관련연구가 증가함에 따라 하나의 관련분야로 규칙기반 시스템 동의 지능적인 웹 환경에 대한 기대 역시 커지고 있다. 하지만 규칙기반 시스템을 활용하기에는 아직도 규칙습득이 많은 제약이 되고 있다. 규칙습득은 웹으로부터 필요한 규칙을 습득하는 일련의 방법인데, 이러한 규칙을 습득하기 위해서는 규칙구성요소를 먼저 식별해야만 한다. 그러나 이러한 규칙을 식별하는 작업은 대부분 지식관리자의 수작업에 의해 이루어지고 있다. 본 연구의 목적은 웹으로부터 규칙구성요소 식별을 최대한 자동화하고 지식관리자의 수작업을 최소화함으로써 그 부담을 줄여 주는 데 있다. 이러한 방법으로는 온톨로지를 근간으로 하여 웹 페이지와의 문자열 비교, 이러한 비교의 한계를 극복하기 위한 확장등의 방법이 있다. 첫 번째 방법은 온툴로지 기반으로 규칙식별 할 웹 페이지와 비교를 통해 지식관리자의 규칙식별 과정을 최대한 자동화하여 주는 것이다. 여기서 만약 현재 규칙을 식별하고자 하는 웹 사이트와 유사한 시스템의 규칙들을 활용하여 일반화 된 온툴로지가 구축되었다면, 이 온톨로지를 기반으로 규칙을 식별하고자 하는 웹사이트와의 비교를 통해 규칙구성요소를 자동화하여 추출 할 수 있다. 이러한 온툴로지를 기반으로 규칙을 식별하기 위해서는 문자열 비교 기법을 사용하게 된다. 하지만 단순한 문자열 비교 기법만으로는 규칙을 식별하는 데에 자연어 처리에 대한 한계가 있다. 이를 극복하기 위해 다음의 두 번째 방법을 사용하고자 한다. 두 번째 방법은 정형화되지 않은 정보들을 확장하여 사용하는 것이다. 우선 찾고자 하는 단어들의 원형을 찾기 위한 스테밍 알고리즘 기법, WordNet을 이용하여 동의어 유의어등으로 확장을 하는 WordNet Expansion 기법, 의미 유사도를 측정하기 위한 방법인 Semantic Similarity Measure 등을 단계적으로 수행하여 자동화되고 정확한 규칙식별을 하고자 한다. 이러한 방법들의 조합으로 인하여 규칙구성요소 추출이 되지 않을 후보 단어들의 수를 줄여서 보다 더 정확하고, 지능적인 규칙구성요소 추출 방법론을 제시하고 구현하여 지식관리자의 규칙습득에 대한 부담을 줄여 주고자 한다.

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Approximate Top-k Labeled Subgraph Matching Scheme Based on Word Embedding (워드 임베딩 기반 근사 Top-k 레이블 서브그래프 매칭 기법)

  • Choi, Do-Jin;Oh, Young-Ho;Bok, Kyoung-Soo;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.22 no.8
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    • pp.33-43
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    • 2022
  • Labeled graphs are used to represent entities, their relationships, and their structures in real data such as knowledge graphs and protein interactions. With the rapid development of IT and the explosive increase in data, there has been a need for a subgraph matching technology to provide information that the user is interested in. In this paper, we propose an approximate Top-k labeled subgraph matching scheme that considers the semantic similarity of labels and the difference in graph structure. The proposed scheme utilizes a learning model using FastText in order to consider the semantic similarity of a label. In addition, the label similarity graph(LSG) is used for approximate subgraph matching by calculating similarity values between labels in advance. Through the LSG, we can resolve the limitations of the existing schemes that subgraph expansion is possible only if the labels match exactly. It supports structural similarity for a query graph by performing searches up to 2-hop. Based on the similarity value, we provide k subgraph matching results. We conduct various performance evaluations in order to show the superiority of the proposed scheme.

Analysis of Changes in Discourse of Major Media on Park Issues - Focusing on Newspaper Articles Published from 1995 to 2019 - (공원 이슈에 대한 주요 언론의 담론변화분석 - 1995년부터 2019년까지 신문 기사를 중심으로 -)

  • Ko, Ha-jung
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.5
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    • pp.46-58
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    • 2021
  • Parks became essential to people after the introduction of modern parks in Korea. Following mayoral elections by popular vote, issues surrounding parks, such as the creation of parks, have arisen and have been publicized by the media, allowing for the formation of discourse. Accordingly, this study conducted a topic analysis by collecting news articles from major media outlets in Korea that addressed issues related to parks since 1995, after the introduction of mayoral elections by popular vote, and analyzed changes over time in the discourse on parks through semantic network analysis. As a result of a Latent Dirichlet allocation topic modeling analysis, the following five topics were classified: urban park expansion (Topic 1), historical and cultural parks (Topic 2), use programs (Topic 3), zoo event (Topic 4), and conflicts in the park creation process (Topic 5). The park-related discourse addressed by the media is as follows. First, the creation process and conflicts regarding the quantitative expansion of parks are treated as the central discourse. Second, the names of parks appear as keywords every time a new park is created, and they are mentioned continuously from then on, thereby playing an important role in the formation of discourse. Third, 'residents' form discourse about the public nature of the park as the principal agent in park-related media. This study has significance in that it examines how parks are interpreted and how discourse is formed and changed by the media. It is expected that discourse on parks will be addressed from various perspectives in further research focusing on other media, such as regional and specialized magazines.

Personalized Web Search using Query based User Profile (질의기반 사용자 프로파일을 이용하는 개인화 웹 검색)

  • Yoon, Sung Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.2
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    • pp.690-696
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    • 2016
  • Search engines that rely on morphological matching of user query and web document content do not support individual interests. This research proposes a personalized web search scheme that returns the results that reflect the users' query intent and personal preferences. The performance of the personalized search depends on using an effective user profiling strategy to accurately capture the users' personal interests. In this study, the user profiles are the databases of topic words and customized weights based on the recent user queries and the frequency of topic words in click history. To determine the precise meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate the semantic relatedness to words in the user profile. The experiments were conducted by installing a query expansion and re-ranking modules on the general web search systems. The results showed that this method has 92% precision and 82% recall in the top 10 search results, proving the enhanced performance.

Functional Expansion of Morphological Analyzer Based on Longest Phrase Matching For Efficient Korean Parsing (효율적인 한국어 파싱을 위한 최장일치 기반의 형태소 분석기 기능 확장)

  • Lee, Hyeon-yoeng;Lee, Jong-seok;Kang, Byeong-do;Yang, Seung-weon
    • Journal of Digital Contents Society
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    • v.17 no.3
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    • pp.203-210
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    • 2016
  • Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.

Personalized Search Technique using Users' Personal Profiles (사용자 개인 프로파일을 이용한 개인화 검색 기법)

  • Yoon, Sung-Hee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.3
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    • pp.587-594
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    • 2019
  • This paper proposes a personalized web search technique that produces ranked results reflecting user's query intents and individual interests. The performance of personalized search relies on an effective users' profiling strategy to accurately capture their interests and preferences. User profile is a data set of words and customized weights based on recent user queries and the topic words of web documents from their click history. Personal profile is used to expand a user query to the personalized query before the web search. To determine the exact meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate semantic similarities to words in the user personal profile. Experimental results with query expansion and re-ranking modules installed on general search systems shows enhanced performance with this personalized search technique in terms of precision and recall.

A Study of Integration Modelling for Context-aware Service Based on Ontology (온톨로지 기반의 상황인지 서비스를 위한 통합 모델에 관한 연구)

  • Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.253-255
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    • 2015
  • In a variety of network environments, the provision of context-aware services, it is difficult to integrate and share because of the heterogeneity problem between distributed data. This paper proposes the integration model using the ontology as a method for solving the above. This uses an ontology to integrate the context-aware informations that are collected. The ontology is generated by the acquisition, semantic analysis and inference of the metadata of the context-aware information. This is the basis of the analysis and analysis of the additional system. Accordingly, this paper studies ways to create an ontology and apply them. The advantage of the proposed scheme can be used without modifying the existing tools, it is possible to easily perform the expansion and consolidation of the system.

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A Study on the Semantic Analysis of the type of Biomorphic Fashion Design (자연모사적 패션디자인의 유형 및 의미 해석)

  • Kim, Jieun;Lee, Jeehyun
    • Journal of the Korean Society of Costume
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    • v.65 no.4
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    • pp.19-30
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    • 2015
  • In recent years, various studies about 'Biomorphic design' have been conducted and accelerated among many recent design concepts and methodology. Therefore, this study classifies the types of biomorphic fashion design based on literature review, and select biomorphic fashion designs in the latest fashion designer's collection. This study aimed to determine the types and characteristics of the biomorphic design in fashion design, and analyze the characteristics and the interpreted intrinsic meanings through Greimas Semiotic rectangle model based on the Binary-Opposition of meaning and Isotophy. As the result of analysis, biomorphic designs in fashion are classified as three types: 'representational imitation of form', 'technical imitation of functional features', and 'imitation of symbolic attribute'. 'Representational imitation of form' was derived from an organic design through atypical forms, repetition and extension of figurative forms of nature, and 'the functionalities of the nature' are interpreted as the feature to maintain the condition of the life itself and to attempt to regulate the status of self-autonomy. Lastly, 'the imitation of symbolic attributes' is designing the process of creation, growth, expansion and destruction from circulation of nature.

Intelligne information retrieval using latent semantic analysis on the internet (인터넷에서 잠재적 의미 분석을 이용한 지능적 정보 검색)

  • 임재현;김영찬
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.8
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    • pp.1782-1789
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    • 1997
  • Most systems that retrieve distributed information on the Internet have difficulties in retrieving relevant information for they are not able to reflect exact semantics on retrieval queries that usersrequest. In this paepr, we propose an automatic query expansion based on ter distribution which reflects semantics of retrieval term to emhance the performance of information retrieval. We computed weight, indicating its overal imoritance in the collection documents and user's query and we use LSI's SVD technique to measure the term distribution which appears similar to query. And also, we measure the similarity to compared numerical value with query terms. Also we researched the method to reduce additional terms automatically and evaluated the performance of the proposed method.

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