• Journal of KIISE:Databases
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• v.32 no.3
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• pp.297-303
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• 2005

When confronted with a query, question answering systems endeavor to extract the most exact answers possible by determining the answer type that fits with the key terms used in the query. However, the efficacy of such systems is limited by the fact that the terms used in a query may be in a syntactic form different to that of the same words in a document. In this paper, we present an efficient semantic query expansion methodology based on a question category concept list comprised of terms that are semantically close to terms used in a query. The semantically close terms of a term in a query may be hypernyms, synonyms, or terms in a different syntactic category. The proposed system constructs a concept list for each question type and then builds the concept list for each question category using a learning algorithm. In the question answering experiments on 42,654 Wall Street Journal documents of the TREC collection, the traditional system showed in 0.223 in MRR and the proposed system showed 0.50 superior to the traditional question answering system. The results of the present experiments suggest the promise of the proposed method.

• Korean Journal of English Language and Linguistics
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• v.1 no.1
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• pp.59-79
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• 2001

This paper examines syntactic categorial properties of “be” in Korean EFL beginners' utterances. Mainly based upon the acquisition data in Han (2000) and Shin (2000), it proposes that the so-called “S-be-X” construction is a projection of “underdeveloped” functional category F. The projection FP is different from other standard functional categories in that its head is not fully fledged.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.225-230
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• 2020

This paper highlights the influence and the importance of the syntactic-grammatical knowledge on "the reading machine", appeared in Jackendoff (1999). Due to the lack of the detailed testing and implementation in his research, this paper tests an extensive data array using a component of Google Translate, currently available freely and most widely on the internet. Although outdated, Jackendoff's paper, "Why can't Computers use English?", argues that syntactic-grammatical knowledge plays a key role in the outputs of computers and computer-based reading machines. The current research has implemented some testings of his thought-provoking examples, in order to find out whether Google Translate can handle the same problems after two decades or so. As a result, it is argued that in the field of NLP, I-language in the sense of Chomsky (1986, 1995 etc) is real and the syntactic, grammatical, and categorial knowledge is essential in the faculty of language. Therefore, it is reassured in this paper that when it comes to human language, even the most advanced "machine" is still no match for human faculty of language, the syntactic-grammatical knowledge.

• The Journal of Information Systems
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• v.20 no.3
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• pp.41-61
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• 2011

In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.41-67
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• 2006

The writings frame and various rules based on discourse structure and knowledge-based methods were applied to construct the automatic Ext/sums (extracts & summaries) system from the straight news in web. The frame contains the slot and facet represented by the role of paragraphs, sentences , and clauses in news and the rules determining the type of slot. Rearrangement like Unification, separation, and synthesis of the candidate sentences to summary, maintaining the coherence of meanings, was carried out by using the rules derived from similar degree measurement, syntactic information, discourse structure, and knowledge-based methods and the context plots defined with the syntactic/semantic signature of noun and verb and category of verb suffix. The critic sentence were tried to insert into summary.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.1-8
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• 2007

When confronted with a query, question answering systems endeavor to extract the most exact answers possible by determining the answer type that fits with the key terms used in the query. However, the efficacy of such systems is limited by the fact that the terms used in a query may be in a syntactic form different to that of the same words in a document. In this paper, we present an efficient semantic query expansion methodology based on query patterns in a question category concept list comprised of terms that are semantically close to terms used in a query. The proposed system first constructs a concept list for each question type and then builds the concept list for each question category using a learning algorithm. The results of the present experiments suggest the promise of the proposed method.

• Korean Journal of English Language and Linguistics
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• v.1 no.4
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• pp.561-585
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• 2001

It has been claimed recently that the two computational operations Move and Agree of Chomsky (2000, 2001a) should be separated into distinct and independent operations. According to this view, Move is an “operation that applies only to meet an EPP-feature of a functional category.” It is also claimed under that analysis that “a candidate for Move is simply a syntactic object with phonetic content.” The purpose of this short paper is to show that the operation Move should still be viewed as composite; hence it must have the operation Agree as one of its prerequisites. We argue that the EPP feature of T may not be analyzed as an independent feature that triggers overt displacement in syntax. Under Chomsky's (2000, 2001a) theory, displacement in syntax must require the probe-goal (P, G) association before the actual movement takes place. It is shown in this paper that in order for an element $\beta$ to raise to the [Spec, T] position, the $\varphi$-features of T must establish a (P, G) relation with those of $\beta$ prior to movement. In short, Move requires Agree, the EPP feature being dependent on the minimal $\varphi$-feature [person] of nominals.

• Korean Journal of Cognitive Science
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• v.13 no.2
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• pp.15-23
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• 2002

This paper reports an experiment on Broca's aphasics' comprehension of a class of English constructions involving empty categories. Based on Grodzinsky's (1986) account of chance-level performance of agrammatic understanding of movement constructions and their thematic role assignments. I show that Grodzinsky's notion of invisible empty categories can be further extended to include pronomical anaphors (PRO's) in Chomsky's (1981) sense and that the asymmetry in their poor comprehension of subject- and object-control constructions can be explained by the heuristic mechanism of the default thematic role assignment rule. eventually supporting Grodzinsky's claim that empty categories are not visible In agrammatic's syntactic representation.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.255-257
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• 2009

본 논문은 한국어의 통사적 중의성이 언어정보처리에 어떠한 영향을 미치는지 알아보기 위하여 어휘판단과제(lexical decision task)를 실시하였다. 명사의 의미와 동사의 의미로 중의적인 어절을 사용하여 각각의 빈도가 영향을 미치는지를 살펴보고자 하였다. 개별 품사 정보가 모두 영향을 미친다면 각각의 빈도가 영향을 미치게 되고 누적빈도 효과가 발생하여 개별 품사의 빈도와 동일한 비교조건에서의 반응시간보다 빠를 것이다. 실험 결과, 중의어절에서의 반응시간이 가장 빠르게 발생하였고 이를 통해 하나의 중의어절이 의미하는 개별적인 품사 의미가 모두 언어정보처리에 영향을 미친다는 것을 의미한다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3539-3547
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• 1999

Korean linguistic information for the generation modulo of KANT(Knowledge-based Accurate Natural language Translation) system was constructed. As KANT has a language-independent generation engine, the construction of Korean linguistic information means the development of the Korean generation module. Constructed information includes concept-based mapping rules, category-based mapping rules, syntactic lexicon, template rules, grammar rules based on the unification grammar, lexical rules and rewriting rules for Korean. With these information in sentences were successfully and completely generated from the interlingua functional structures among the 118 test set prepared by the developers of KANT system.