• Cross-Cultural Studies
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• v.27
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• pp.387-414
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• 2012

This paper is intended to describe the idiosyncratic aspects of the 'let alone' construction in English, clarifying the productivity property of this construction and to show that this construction displays the properties of prepositional phrase that denote the meaning of 'the comparison of degree', against the claim that this construction should be regarded as a coordinating conjunction. In the process of doing that, this paper classifies this 'let alone' construction into two types of construction, by investigating the external and internal syntactic distributions of 'let alone' constructions as well as the relationship between 'let alone' phrases and the main clause.

• Cross-Cultural Studies
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• v.38
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• pp.501-521
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• 2015

In this paper, through the comparative analysis of Korean syntactic structure of Chinese auxiliary "Aspect" and with this correspondence, find out the semantic differences between the two languages, and the "Aspect" of aspect are analyzed, and results obtained are as follows.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.13-27
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• 1991

DEM(digital elevation map) is a very useful information in various applications. In this paper, we have studied on the terrain matching algorithm using the DEM, which was proposed by Rodriguez and Aggarwal(1990) for an aircraft navigation system. We evaluated its performance using syntactic images. Cliff maps and critical points are used for the reduction of computation time and information size to be processed. The computer simulation shows that though the computational complexity is high, the technique is efficient even to noisy images.

• Journal of English Language & Literature
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• v.57 no.6
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• pp.959-976
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• 2011

The expression no matter, combining with an interrogative clause X, expresses 'it doesn't matter what the value is of X' and displays many syntactic and semantic peculiarities. To better understand the grammatical properties of the construction in question, we investigate English corpora available online and suggest that some of the irreducible properties the construction displays can be best captured by the inheritance mechanism which plays a central role in the HPSG and Construction Grammar. We show that the construction in question has its own constructional properties, but also inherits properties from related major head constructions.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.365-374
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• 2008

In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.642-652
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• 2009

In order to improve the performance of the existing relation extraction approaches, we propose a method for combining two pivotal concepts which play an important role in classifying semantic relationships between entities in text. Having built a composite kernel-based relation extraction system, which incorporates both entity features and syntactic structured information of relation instances, we define nine classes of lexical features and synthetically apply them to the system. Evaluation on the ACE RDC corpus shows that our approach boosts the effectiveness of the existing composite kernels in relation extraction. It also confirms that by integrating the three important features (entity features, syntactic structures and contextual lexical features), we can improve the performance of a relation extraction process.

• The Journal of Society for e-Business Studies
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• v.13 no.1
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• pp.1-20
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• 2008

Ontologies are expected in various areas as promising tools to improve communication among people and to achieve interoperability among systems. For communications between different business domains, building an ontology through integrating existing ontologies is more efficient way than building the ontology without them. However, integration of ontologies is very struggling work since languages, domains, and structures of ontologies are different from each other. In this paper, we suggest an Ontology Architecture which solves this problem by providing a systematic framework to classify ontologies from three kinds of viewpoints : language, domain range, constructs. The Ontology Architecture consists of 3 axes according to the 3 viewpoints : Ontology Meta Layer axis, Semantic Domain Layer axis, and Ontology Constructs Layer axis. Because 3 axes in Ontology Architecture are designed to improve the syntactic and semantic interoperability among ontologies, the integration of ontologies can be readily achieved.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1339-1353
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• 2004

< TABLE > tags in HTML documents are widely used for formatting layout of Web documents as well as for describing genuine tables with relational information. As a prerequisite for information extraction from the Web, this paper presents an efficient method for sophisticated table detection. The proposed method consists of two phases: preprocessing and attribute-value relations extraction. For the preprocessing where genuine or ungenuine tables are filtered out, appropriate rules are devised based on a careful examination of general characteristics of < TABLE > tags. The remaining is detected at the attribute-value relations extraction phase. Specifically, a value area is extracted and checked out whether there is a syntactic coherency Futhermore, the method looks for a semantic coherency between an attribute area and a value area of a table that may be inappropriate for the syntactic coherency checkup. Experimental results with 11,477 < TABLE > tags from 1,393 HTML documents show at the method has performed better compared with previous works, resulting in a precision of 97.54% and a recall of 99.22% in average.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.2876-2884
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• 2000

Clausal segmentation is the method that parses Korean sentences by segmenting one long sentence into several phrases according to the predicates. So far most of researches could be useful for literary sentences, but long sentences increase complexities of the syntax analysis. Thus this paper proposed Two-Level Clausal Segmentation using sense information which was designed and implemented to solve this problem. Analysis of clausal segmentation and understanding of word senses can reduce syntactic and semantic ambiguity. Clausal segmentation using Sense Information is necessary because there are structural ambiguity of sentences and a frequent abbreviation of auxiliary word in common sentences. Two-Level Clausal Segmentation System(TLCSS) consists of Complement Selection Process(CSP) and Noncomplement Expansion Process(NEP). CSP matches sentence elements to subcategorization dictionary and noun thesaurus. As a result of this step, we can find the complement and subcategorization pattern. Secondly, NEP is the method that uses syntactic property and the others methods for noncomplement increase of growth. As a result of this step, we acquire segmented sentences. We present a technique to estimate the precision of Two-Level Clausal Segmentation System, and shows a result of Clausal Segmentation with 25,000 manually sense tagged corpus constructed by ETRl-KONAN group. An Two-Level Clausal Segmentation System shows clausal segmentation precision of 91.8%.