• 말소리와 음성과학
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• 제7권4호
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• pp.49-55
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• 2015

It is argued in this paper that, in determining semantic similarity, Korean words should be recategorized with a focus on the semantic relation to ontology in light of cross-linguistic morphological variations. It is proposed, in particular, that Korean semantic similarity should be measured on three tracks, human judgements track, relatedness track, and cross-part-of-speech relations track. As demonstrated in Yang et al. (2015), GloVe, the unsupervised learning machine on semantic similarity, is applicable to Korean with its performance being compared with human judgement results. Based on this compatability, it was further thought that the model's performance might most likely vary with different kinds of specific relations in different languages. An attempt was made to analyze them in terms of two major Korean-specific categories involved in their lexical and cross-POS-relations. It is concluded that languages must be analyzed by varying methods so that semantic components across languages may allow varying semantic distance in the vector space models.

• 전기학회논문지
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• 제58권3호
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• pp.632-638
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• 2009

Probabilistic Latent Semantic Analysis has many applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. In this paper, we propose an algorithm using weighted Probabilistic Latent Semantic Analysis Model to find the contextual phrases and opinions from documents. The traditional keyword search is unable to find the semantic relations of phrases, Overcoming these obstacles requires the development of techniques for automatically classifying semantic relations of phrases. Through experiments, we show that the proposed algorithm works well to discover semantic relations of phrases and presents the semantic relations of phrases to the vector-space model. The proposed algorithm is able to perform a variety of analyses, including such as document classification, online reputation, and collaborative recommendation.

• International Journal of Contents
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• 제2권1호
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• pp.22-28
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• 2006

In this paper, we propose new semantic contents modeling using individual features, associative relations and visual features for efficiently supporting browsing and retrieval of video semantic contents. And we implement and design a browsing and retrieval system based on the semantic contents modeling. The browsing system supports annotation based information, keyframe based visual information, associative relations, and text based semantic information using a tree based browsing technique. The retrieval system supports text based retrieval, visual feature and associative relations according to the retrieval types of semantic contents.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.129-148
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• 2016

Acute myocardial infarction (AMI) is one of the three emergency diseases that require urgent diagnosis and treatment in the golden hour. It is important to identify the status of the coronary artery in AMI due to the nature of disease. Therefore, multi-modal medical images, which can effectively show the status of the coronary artery, have been widely used to diagnose AMI. However, the legacy system has provided multi-modal medical images with flat and unstructured data. It has a lack of semantic information between multi-modal images, which are distributed and stored individually. If we can see the status of the coronary artery all at once by integrating the core information extracted from multi-modal medical images, the time for diagnosis and treatment will be reduced. In this paper, we analyze semantic relations between multi-modal medical images based on coronary anatomy for AMI. First, we selected a coronary arteriogram, coronary angiography, and echocardiography as the representative medical images for AMI and extracted semantic features from them, respectively. We then analyzed the semantic relations between them and defined the convergence data model for AMI. As a result, we show that the data model can present core information from multi-modal medical images and enable to diagnose through the united view of AMI intuitively.

• 한국문헌정보학회지
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• 제47권3호
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• pp.343-361
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• 2013

본 연구는 스피치 요약을 위해서 태그를 확장하고 또한 태그 간의 의미적 관계 정보를 이용할 수 있는 태그의미분석 방법을 제안하고 평가하였다. 이를 위해서, 먼저 비디오 태그를 확장하고 태그 간의 의미적 관계를 분석하는데 있어서 플리커의 태그 클러스터와 워드넷의 동의어 정보가 얼마나 효과적으로 이용될 수 있는가 조사해 보았다. 그런 다음 태그의미분석 방법의 특성과 효율성을 조사해 보기 위해서 제안한 방법을 잠재의미분석(Latent Semantic Analysis) 방법과 비교해 보았다. 분석 결과, 플리커의 태그 클러스터는 효과적으로 이용되었지만 워드넷은 효과적으로 이용되지 못한 것으로 나타났다. F측정을 사용하여 두 방법의 효율성을 비교한 결과, 제안한 방법의 F값(0.27)이 잠재의미분석 방법의 F값(0.22)보다 높게 나타났다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권10호
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• pp.627-635
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• 2008

본 연구에서는 사용자 어휘지능망(U-WIN)의 어휘 관계 중의 하나인 구문관계를 자동으로 구축하는 방법을 제시하고자 한다. 먼저, 구문관계를 형성할 수 있는 후보명사를 용언의 용례에서 문형 정보를 기준으로 추출함으로써, 용언의 세분화된 의미별로 정확하고 다양한 후보명사를 추출할 수 있다. 그러나 추출된 후보명사는 다양한 의미를 지니고 있으므로, 어휘간의 명확한 구문관계를 설정하기 위해서는 후보명사의 여러 의미 중에서 정확한 의미로 결정해야 한다. 그래서 본 연구에서는 용례 매칭 규칙, 구문 패턴, 의미 유사도, 빈도 정보 등을 이용하여 후보명사의 의미를 분별한다. 또한 구문패턴의 빈도 정보를 이용하여 용례에 나타나지 않지만 구문관계를 형성할 수 있는 명사를 추출하여 구문관계를 확장하고자 하였다. 이러한 연구는 명사 중심의 어휘망이 용언과의 구문관계 구축을 통해 형태소 분석, 구문 분석, 의미분석 등에 광범위하게 활용할 수 있는 어휘망의 기반을 다지는 작업이 될 수 있을 것이다.

• 한국언어정보학회지:언어와정보
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• 제17권2호
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• pp.29-50
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• 2013

Multiple Nominative Constructions (MNCs) and Multiple Accusative Constructions (MACs) have been some of the hottest and interesting topics in Korean syntax. This paper took empirical approaches to these constructions and examined native speakers' grammaticality judgements of these constructions. Though there are lots of previous studies on these constructions, Ryu (2010, 2013a, 2013b, 2013c) recently tried to unify MNCs and MACs into Multiple Case Constructions (MCCs) and to classify them into 16 types based on the semantic relations. This paper includes experiments which were performed on these 16 different types. The experiments were designed following Johnson (2008); and the native speakers' intuition was measured with two scales, numerical estimates and line drawing, though the latter was adopted in the actual analyses. Through the experiment, the following facts were observed: (i) the grammaticality of the MCCs varies depending on their semantic relations, (ii) MNCs were more grammatical than MACs if both constructions occurred in similar environments, and (iii) the sentences in some MAC types had much lower grammaticality than those in the others, as Ryu (2013b, 2013c) mentioned.

• 한국언어정보학회지:언어와정보
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• 제17권1호
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• pp.1-16
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• 2013

The goal of this paper is two-fold: (i) the paper aims to characterize unique semantics of so called "symmetric" locatives like across the street - this will provide a guiding semantics for annotating a variety of paths; and (ii) the paper claims that we need "symmetric" paths to give a unified account of the various semantic effects of symmetric locatives. The paper illustrates several semantic effects induced by symmetric locatives: (i) symmetric underspecification, (ii) path-/event-quantification, (iii) static symmetric relations, and (iv) the symmetric inference by the adverb back. The paper defines the semantic class of symmetric locatives, and accounts for the symmetry effects in terms of properties and relations of Path Structure proposed by Nam (1995).

• 인지과학
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• 제10권1호
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• pp.45-55
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• 1999

본 논문은 사건/사타에 대한 공간적 인지가 수행되는 기본적인 방식을 규명하기 위해서는 그 사건/사태에 참여하는 참가자의 위치가 가장 주요한 요인임을 주장하고, 자연언어는 공간적 인지를 표현하기 위해 비교적 "단순한" 의미유형을 사용하고 있으며, 공간표현을 해석할 때 사건/사태 전체의 위치를 지정하는 것으로 해석하지 않고, 그 참가자로 표현된 논항(arguments)의 위치를 지정하는 것으로 해석한다는 것이다. 본 논문은 장소표현이 타동사의 두 논항의 위치를 지정하는 방식을 네 가지 유형의 노항지향성(argument orientations)으로 분류하여 기술하였고, 논항지향성을 통하여 영어를 포함한 자연언어의 장소표현이 관계(relations)의 집합에서 관계의 집합으로 사상하는 교차함수(intersecting functioins)로 해석되어야 한다는 의미해석상의 제약이 있음을 밝히고 있다.

• 디지털산업정보학회논문지
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• 제6권1호
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.