• Korean Linguistics
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• v.80
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• pp.151-175
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• 2018

This paper proposed a method of semantic recognition to improve the extraction of correct answers of the Q&A system through machine learning. For this purpose, the semantic recognition method is described based on the distribution of predicative nouns. Predicative noun vocabularies and sentences were collected from Wikipedia documents. The predicative nouns are typed by analyzing the environment in which the predicative nouns appear in sentences. This paper proposes a semantic recognition method of predicative nouns to which rules can be applied. In Chapter 2, previous studies on predicative nouns were reviewed. Chapter 3 explains how predicative nouns are distributed. In this paper, every predicative nouns that can not be processed by rules are excluded, therefore, the predicative nouns noun forms combined with the case marker '의' were excluded. In Chapter 4, we extracted 728 sentences composed of 10,575 words from Wikipedia. A semantic analysis engine tool of ETRI was used and presented a predicative nouns noun that can be handled semantic recognition language.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.451-457
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• 2005

In spite of the development of computers, the present state that a lot of electronic documents are overflowing makes it more difficult for us to get appropriate information. Therefore, it's more important to focus on getting meaningful information than processing the data quickly In this context, Semantic Web enables an intelligent processing by adding semantic metadata on yow web documents. Also, as the Semantic Web grows, the knowledge resources as well as web resources are getting more and more importance. In this paper, we propose an OWL storage system aiming at an intelligent Processing by adding semantic metadata on your web documents, plus a system aiming at an OWL-QL Query Processing.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.531-538
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• 2016

In this paper, we propose a novel post-processing method of semantic segmentation from indoor scenes with RGBD inputs. For accurate segmentation, various post-processing methods such as superpixel from color edges or Conditional Random Field (CRF) method considering neighborhood connectivity have been used, but these methods are not efficient due to high complexity and computational cost. To solve this problem, we maximize the efficiency of post processing by using depth superpixel extracted from disparity image to handle object silhouette. Our experimental results show reasonable performances compared to previous methods in the post processing of semantic segmentation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2761-2781
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• 2018

With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.

• Annual Conference of KIPS
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• 2009.11a
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• pp.523-524
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• 2009

Peer-to-Peer(P2P) 시스템은 분산된 대용량 데이터를 효율적으로 공유하게 하여 사용자들에게 제공되는 killer application 으로 최근까지 여러 분야에서 연구가 되고 있다. 하지만 P2P 네트워크에서 피어가 소유한 데이터나 공통 관심사 또는 사회적인 관계를 고려하지 않고 무작위로 오버레이가 구성되기 때문에 검색 결과의 제약이 발생한다. 따라서 본 논문에서는 P2P 오버레이상의 효율적인 데이터 검색을 위해서 각 피어가 가지고 있는 데이터와 공통의 관심사를 기반으로 유사성을 측정하여 semantic overlay를 구성하는 기법을 제안한다. 그리고 피어들 간의 semantic proximity는 데이터 요약 기법을 사용하여 측정되며 측정 과정상에서 popular content을 고려하여 semantic proximity의 왜곡현상을 방지하여 semantic link quality의 향상을 가져오는 방안을 도입한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.11-20
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• 2010

Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

• Language and Information
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• v.9 no.1
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• pp.19-34
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• 2005

Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. However, ontology construction requires vast amount of data collection and arduous efforts in processing these un-structured data. This study proposed a methodology to automatically construct and generate ontologies from Sejong Electronic Dictionary. As Sejong Electronic Dictionary is structured in XML format, it can be processed automatically by computer programmed tools into an OWL(Web Ontology Language)-based ontologies as specified in W3C . This paper presents the process and concrete application of this methodology.

• Annual Conference of KIPS
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• 2012.04a
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• pp.305-308
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• 2012

스마트폰 사용자가 급증함에 따라 스마트폰을 중심으로 한 스마트 모바일 서비스 개발이 활발하게 진행되고 있다. 스마트 모바일 서비스를 제공하기 위해 필요한 가장 중요한 기술 중 하나는 지능적인 의미처리이다. 현재 의미처리를 위한 접근방법으로는 유사도 기반, 어댑터 기반, 정적 의미 관리 기반 및 동적 의미 관리 기반 접근방법이 있다. 이 논문에서는 이러한 접근 방법 중 MDR 기반의 의미처리 접근방법인 동적 의미 관리 기반을 이용한 응용서비스를 구현한다. Semantic Sign-up 응용서비스를 구현함으로써 동적 의미 관리의 장점을 명확히 보이고 사용자에게 편리성을 제공한다.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.13-28
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• 2007

This is a speculative paper, describing a recently started effort to give a formal semantics to semantic annotation schemes. Semantic annotations are intended to capture certain semantic information in a text, which means that it only makes sense to use semantic annotations if these have a well-defined semantics. In practice, however, semantic annotation schemes are used that lack any formal semantics. In this paper we outline how existing approaches to the annotation of temporal information, semantic roles, and reference relations can be integrated in a single XML-based format and can be given a formal semantics by translating them into second-order logic. This is argued to offer an incremental aproach to the incorporation of semantic information in natural language processing that does not suffer from the problems of ambiguity and lack of robustness that are common to traditional approaches to computational semantics.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.31-41
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• 2009

In the Semantic Web, it is possible to provide intelligent information retrieval and automated web services by defining a concept of information resource and representing a semantic relation between resources with meta data and ontology. It is very important to manage semantic data such as ontology and meta data efficiently for implementing essential functions of the Semantic Web. Thus we propose an index structure to support more accurate search results and efficient query processing by considering semantic and structural features of the semantic data. Especially we use a graph data model to express semantic and structural features of the semantic data and process various type of queries by using graph model based path expressions. In this paper the proposed index aims to distinguish our approach from earlier studies and involve the concept of the Semantic Web in its entirety by querying on primarily extracted structural path information and secondary extracted one through semantic inferences with ontology. In the experiments, we show that our approach is more accurate and efficient than the previous approaches and can be applicable to various applications in the Semantic Web.