• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1996년도 Language, Information and Computation = Selected Papers from the 11th Pacific Asia Conference on Language, Information and Computation, Seoul
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• pp.53-62
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• 1996

• 한국영어학회지:영어학
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• 제3권1호
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• pp.89-108
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• 2003

As pronouns are resolved with their antecedents, definite NPs may enter into the anaphora-antecedent relations with indefinite NPs. This paper is to provide faster and more efficient computational algorithms by which definite NPs are resolved effectively, For this purpose, this paper extends Chierchia's Binding Theory in Categorial Grammar, and definite NPs are resolved with their antecedents by similar algorithms that are used to reflexive resolution. In these algorithms, the relations between indefinite NP and definite NP are represented with λ-expressions, and definite NPs are resolved with their antecedent by λ-conversions.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2001년도 학술대회 논문집
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• pp.231-235
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• 2001

Language is not abstract. We use language to communicate out thoughts and emotions. Films are the most public form of arts, where language is all essential part; however, there have been, if any, few films the main theme of which is language. Although language may not be the main theme of films, we can find many kinds of information relating to language and linguistics by careful examination. In reference to some films, we can talk about subjects in the fields of theoretical linguistics such as phonetics, phonology, morphology, syntax, semantics, and pragmatics. In addition, subjects in applied linguistics such as sociolinguistics and computational linguistics may be discussed with reference to other films.

• Genomics & Informatics
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• 제17권2호
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• pp.21.1-21.6
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• 2019

Dependency parsing is often used as a component in many text analysis pipelines. However, performance, especially in specialized domains, suffers from the presence of complex terminology. Our hypothesis is that including named entity annotations can improve the speed and quality of dependency parses. As part of BLAH5, we built a web service delivering improved dependency parses by taking into account named entity annotations obtained by third party services. Our evaluation shows improved results and better speed.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.21-38
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• 2006

Programmed grammars, one of the most important and well investigated classes of grammars with context-free rules and a mechanism controlling the application of the rules, can be described by graphs. We investigate whether or not the restriction to special classes of graphs restricts the generative power of programmed grammars with erasing rules and without appearance checking, too. We obtain that Eulerian, Hamiltonian, planar and bipartite graphs and regular graphs of degree at least three are pr-universal in that sense that any language which can be generated by programmed grammars (with erasing rules and without appearance checking) can be obtained by programmed grammars where the underlying graph belongs to the given special class of graphs, whereas complete graphs, regular graphs of degree 2 and backbone graphs lead to proper subfamilies of the family of programmed languages.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.126-135
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• 2007

We propose and test several computational methods to automatically determine possible saliency cut-off points in Sketch Engine (Kilgarriff and Tugwell, 2001). Sketch Engine currently displays collocations in descending importance, as well as according to grammatical relations. However, Sketch Engine does not provide suggestions for a cut-off point such that any items above this cut-off point may be considered significantly salient. This proposal suggests improvement to the present Sketch Engine interface by calculating three different cut-off point methods, so that the presentation of results can be made more meaningful to users. In addition, our findings also contribute to linguistic analyses based on empirical data.

• 한국영어학회지:영어학
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• 제4권2호
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• pp.175-194
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• 2004

This paper provides computational algorithms for English Questions, by which we can effectively handle and implement Yes-No Questions and Wh-Questions. Those algorithms will be developed in Categorial Grammar. In this paper, we will modify and revise Steedman＇s Combinatory Categorial Grammar (CCG) so that we can computationally implement Questions effectively, which will be called a CCG-like system. In this system, semantic interpretations of Questions will be calculated compositionally based on the functor-arguments relations of the constituents. In sum, this paper provides analyses of Questions in Categorial Grammar, by which we can effectively implement Questions in English.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1995년도 Language, Information and Computation = Proceedings of the 10th Pacific Asia Conference, Hong Kong
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• pp.273-280
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• 1995

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1996년도 Language, Information and Computation = Selected Papers from the 11th Pacific Asia Conference on Language, Information and Computation, Seoul
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• pp.109-118
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• 1996

• International Journal of Contents
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• 제15권1호
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• pp.39-51
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• 2019

Spontaneous speech provides rich information defining the linguistic characteristics of individuals. As such, computational analysis of speech would enhance the efficiency involved in evaluating patients' speech. This study aims to provide a method to differentiate the persons with and without aphasia based on language usage. Ten aphasic patients and their counterpart normal controls participated, and they were all tasked to describe a set of given words. Their utterances were linguistically processed and compared to each other. Computational analyses from PCA (Principle Component Analysis) to machine learning were conducted to select the relevant linguistic features, and consequently to classify the two groups based on the features selected. It was found that functional words, not content words, were the main differentiator of the two groups. The most viable discriminators were demonstratives, function words, sentence final endings, and postpositions. The machine learning classification model was found to be quite accurate (90%), and to impressively be stable. This study is noteworthy as it is the first attempt that uses computational analysis to characterize the word usage patterns in Korean aphasic patients, thereby discriminating from the normal group.