• Korean Journal of English Language and Linguistics
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• v.4 no.1
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• pp.1-31
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• 2004

This paper has revisited the dative alternation in English, and defended the so-called polysemy view. The paper has argued for a particular format of lexical representation, one that allows reference to events. In addition to the semantic conditions, the paper has argued that the DO and PO constructions also allow for different information structures.

• Proceedings of the Korean Society for Language and Information Conference
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• 2001.06a
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• pp.185-197
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• 2001

It is quite burden-some for non-native speakers of English to write and read more and more IT-related reports due to the rapid development of IT technology. Thus, this study aims at designing ESP materials by using huge volume of electronic ITU texts, corpora and concordancer SW. Various tests are designed to study the usage of articles, hyponym, agreement, synonym, and others. The results of this study will bring general and practical benefits to technical English writing and improving IT area students' lexical knowledge of actual English usage. The ESP materials produced by this study will also make an extensive contribution to other industries and academic areas in Korean society.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.201-203
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• 1998

한국어의 의미 분석을 위해서 의미소가 부여된 말뭉치(Sense-Tagged Corpus)의 구축은 필수적이다. 의미 태깅은 어휘의 다의적 특성으로 인해, 형태소나 구문 태깅에서와 같은 규칙 기반의 처리가 어려웠다. 기존의 연구에서 어휘의 의미는 형태소와 구문적 제약 등의 표층상에서 파악되어 왔으며, 이는 의미 데이터 기반으로 이루어진 것이 아니었기에, 실용적인 결과를 얻기가 힘들었다. 본 연구는 한국어의 구문과 의미적 특성을 고려하고, 용언과 모어 성분간의 의존 관계 및 의미 정보를 나타내는 하위범주화사전과 어휘의 계층적 의미 관계를 나타낸 의미사전(시소러스)을 이용하여, 반자동적인 방법으로 의미소가 부여된 말뭉치의 구축을 위한 기준과 알고리즘을 논하고자 한다.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.223-233
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• 2007

The so-called Korean BNC (bound noun construction) displays complex syntactic, semantic, and constructional properties. This paper, couched upon a constraint-based approach, two different syntactic structures for the construction with articulated lexical properties for the BNs and relevant predicates. The paper reports an implementation of this analysis in the LKB (Linguistic Knowledge Building) system and shows us that this direction is robust enough to pare relevant sentences.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.463-465
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• 2002

자동 문서 요약 시스템은 문서내 담겨있는 정보를 최대만 표현하면서 문서의 크기를 줄이는 시스템이다. 본 논문에서는 어휘를 자동으로 클러스터링하여 문서 대표어를 찾고, 이를 제목과 조합하여 요약을 수행하는 시스템을 제안한다. 특히 이 시스템은 제목이 없는 문서도 요약을 수행할 수 있는 장점이 있다. 비교시스템으로는 제목, 위치, 빈도를 이용만 시스템을 구축하여 사용하였으며 30%, 10%, 그리고 4문장 요약에서 제안한 시스템은 모두 우수한 성능을 보였다.

• Korean Journal of Cognitive Science
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• v.26 no.1
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• pp.1-26
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• 2015

The purpose of this study was to examine whether the phonological information or the orthographic information plays a major role in visual word recognition. To do so, we used a non-word lexical decision task(LDT) in Experiment 1 and masked priming tasks in Experiement 2 and 3. The results of Experiment 1 showed that reaction times and the error rates were affected by the orthographic characteristics of the non-word stimuli such that orthographically similar non-words condition showed prolonged reaction times and higher error rates than control condition. In Experiment 2 and Experiment 3, the participants performed masked priming lexical decision tasks in two SOA conditions(60ms, 150ms). The results of the both experiments showed that the orthographically identical first syllable priming facilitated lexical decision of the target words while both of the pseudo-homophone priming and the phonologically identical first syllable priming did not. The dual route hypothesis(Coltheart et al, 2001), assuming that orthographic information rather than phonological information is the major source for the visual word recognition processes, fits well with the results of the current study.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.865-872
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• 2013

Two-level morphology analysis method is one of rule-based morphological analysis method. This approach handles morphological transformation using rules and analyzes words with morpheme connection information in a lexicon. It is independent of language and Korean Two-level system was also developed. But, it was limited in practical use, because of using very small set of lexicon built manually. And it has also a over-generation problem. In this paper, we propose an automatic construction method of Korean Two-level lexicon for PC-KIMMO from morpheme tagged corpus. We also propose a method to solve over-generation problem using lexical information and sub-tags. The experiment showed that the proposed method reduced over-generation by 68% compared with the previous method, and the performance increased from 39% to 65% in f-measure.

• Journal of KIISE
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• v.42 no.6
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• pp.817-822
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• 2015

Relation extraction is an important information extraction technique that can be widely used in areas such as question-answering and knowledge population. Previous studies on relation extraction have been based on supervised machine learning models that need a large amount of training data manually annotated with relation categories. Recently, to reduce the manual annotation efforts for constructing training data, distant supervision methods have been proposed. However, these methods suffer from a drawback: it is difficult to use these methods for collecting negative training data that are necessary for resolving classification problems. To overcome this drawback, we propose a one-class classification model that can be trained without using negative data. The proposed model determines whether an input data item is included in an inner category by using a similarity measure based on lexical information and syntactic patterns in a vector space. In the experiments conducted in this study, the proposed model showed higher performance (an F1-score of 0.6509 and an accuracy of 0.6833) than a representative one-class classification model, one-class SVM(Support Vector Machine).

• Journal of the Korean Institute of Telematics and Electronics
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• v.16 no.3
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• pp.1-8
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• 1979

This is Part I of a two-part article on Korean character processing by a computer. In part I, the problems in Korean character processing are identified and the theoretical foundation is laid out as a viable solution to them. The one-and two-dimensional syntactic structures of Korean characters are formally defined by means of BNF and " Patternal structure " respectively. Formal discussion of lexical and syntactic algorithms is given for character conversion. This character conversion algorithm is applicable to both input and output. For device-independence and implementation-independence, the concept of " cardinal symbol set " is introduced. We will present a historical survey of Korean character processing and discussion of implementation problems for the above algorithm In Part II.lgorithm In Part II.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.49-59
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• 2000

The majority of work done to date on natural language processing has focused on analysis and understanding of language, thus natural language generation had been relatively less attention than understanding, And people even tends to regard natural language generation CIS a simple reverse process of language understanding, However, need for natural language generation is growing rapidly as application systems, especially multi-language machine translation systems on the web, natural language interface systems, natural language query systems need more complex messages to generate, In this paper, we propose an algorithm to generate more flexible and natural sentence using lexical functions of Igor Mel'uk (Mel'uk ＆ Zholkovsky, 1988) and systemic grammar.