• Journal of KIISE:Software and Applications
• /
• v.28 no.5
• /
• pp.448-448
• /
• 2001

The definitions in Korean dictionary not only describe meanings of title, but also include various semantic information such as hypernymy/hyponymy, meronymy/holonymy, polysemy, homonymy, synonymy, antonymy, and semantic features. This paper purposes to implement a parser as the basic tool to acquire automatically the semantic information from the definitions in Korean dictionary. For this purpose, first we constructed the part-of-speech tagged corpus and the tree tagged corpus from the definitions in Korean dictionary. And then we automatically extracted from the corpora the frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability based on the statistical method. The parser is a kind of the probabilistic chart parser that uses the extracted data. The frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability resolve the noun phrase's structural ambiguity during parsing. The parser uses a grammar factoring, Best-First search, and Viterbi search In order to reduce the number of nodes during parsing and to increase the performance. We experiment with grammar rule's probability, left-to-right parsing, and left-first search. By the experiments, when the parser uses grammar rule's probability and left-first search simultaneously, the result of parsing is most accurate and the recall is 51.74% and the precision is 87.47% on raw corpus.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.2
• /
• pp.49-59
• /
• 2007

This paper is about an system which can perform automatic semantic annotation to actualize "Semantic Web." Since it is impossible to tag numerous documents manually in the web, it is necessary to gather large Korean web documents as training data, and extract features by using natural language techniques and a thesaurus. After doing these, we constructed concept classifiers through the SVM (support vector machine) teaming algorithm. According to the characteristics of Korean language, morphological analysis and syntax analysis were used in this system to extract feature information. Based on these analyses, the concept code is mapped with Kadokawa thesaurus, which made it possible to map similar words and phrase to one concept code, to make training vectors. This contributed to rise the recall of our system. Results of the experiment show the system has a some possibility of semantic annotation.

• The Journal of Korean Association of Computer Education
• /
• v.21 no.6
• /
• pp.105-115
• /
• 2018

The descriptive-type question is appropriate for deep thinking ability evaluation, but it is not easy to grade. Since, even though same grading criterion, the graders produce different scores, we need the objective evaluation system. However, the system needs the Korean analysis. As the descriptive-type answering is described with the compound sentence, the system has to analyze the compound sentence. This paper develops the Korean syntactic-semantic analysis system for compound sentence and evaluates performance of the system. This system selects the modifiee of the word phrase using syntactic-semantic constraint and semantic dictionary. The 93% accurate rate shows that the system is effective. This system will be utilized in descriptive-type grading and Korean processing.

• Speech Sciences
• /
• v.8 no.2
• /
• pp.149-163
• /
• 2001

This paper investigates the manner in which various. syntactic structures with a single meaning implement a consistent intonational pattern by examining English conditional clauses. In the phonetic experiment, we explore the edge tones in three different syntactic clauses which are semantically interpreted as a single conditional meaning (an if-clause, a clause with no if. and a clause with no if but followed by and) and compare them with the edge tone realized in a clause which is not interpreted as a conditional meaning. We also investigate the tonal differences resulting from the semantic difference between conditional and non-conditional meanings. That is, the conditional clauses expressed in three different syntactic structures show a consistent intonational pattern in their clausefinal boundaries; a rising contour (H- or H%) is realized at the edge of the intermediate phrases (ip) or intonational phrases (IP) in 89% of the if-clauses, 72% of the clauses with no if, and 79% of the clauses with no if but followed by and. On the other hand, 82% of the non-conditional clauses have a falling contour (L- or L-L%) in their final edge. Statistically, Chi-Square tests show that these percentages are all significantly higher, which suggests that a conditional meaning implements a consistent intonational pattern though it is expressed through different syntactic structures. Therefore, the result supports Bolinger's (1989) claim that intonation makes an important contribution to discourse interpretation.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2008.10a
• /
• pp.90-93
• /
• 2008

In natural language, it is common that repetitive constituents in an expression are to be left out and it is necessary to figure out the constituents omitted at analyzing the meaning of the sentence. This paper is on recognition of boundaries of parallel noun phrases by figuring out constituents omitted. Recognition of parallel noun phrases can greatly reduce complexity at the phase of sentence parsing. Moreover, in natural language information retrieval, recognition of noun with modifiers can play an important role in making indexes. We propose an unsupervised probabilistic model that identifies parallel cores as well as boundaries of parallel noun phrases conjoined by a conjunctive particle. It is based on the idea of swapping constituents, utilizing symmetry (two or more identical constituents are repeated) and reversibility (the order of constituents is changeable) in parallel structure. Semantic features of the modifiers around parallel noun phrase, are also used the probabilistic swapping model. The model is language-independent and in this paper presented on parallel noun phrases in Korean language. Experiment shows that our probabilistic model outperforms symmetry-based model and supervised machine learning based approaches.

• Convergence Security Journal
• /
• v.19 no.1
• /
• pp.31-40
• /
• 2019

Today, information security (INFOSEC) as a discipline is gaining more and more importance according to the emergence and extension of the cyberspace. Originated from Joint Doctrine for Information Operation (Joint Pub 3-13) by the U.S. Department of Defense, 'information assurance (IA)' is the concept widely used in the relevant field. Grown from the practice of information security, it encompasses broader and more proactive protection that includes countermeasures and repair, security management throughout an information system (IS)'s life-cycle, and trustworthiness of an IS in the process of risk analysis. In Korea, many industry professionals tend to misunderstand IA, remaining unaware of the conceptual differences between IA and INFOSEC. On this account, the current study attempted to provide a combined definition of IA by reviewing relevant literature. This study showed the validity of the wordings used in the proposed definition phrase by phrase.

• The KIPS Transactions:PartB
• /
• v.14B no.7
• /
• pp.559-566
• /
• 2007

Subjective sentences express opinions, emotions, evaluations and other subjective ideas relevant to products or events. These expressions sometimes can be seen in only part of a sentence, thus extracting features from a full-sentence can degrade the performance of subjective-sentence-classification. This paper presents a method for improving the performance of a subjectivity classifier by combining two classifiers generated from the different representations of an input sentence. One representation is a sentimental phrase that represents an automatically identified subjective expression or objective expression and the other representation is a full-sentence. Each representation is used to extract modified n-grams that are composed of a word and its contextual words' polarity information. The best performance, 79.7% accuracy, 2.5% improvement, was obtained when the phrase-level classifier and the sentence-level classifier were merged.

• Journal of Digital Contents Society
• /
• v.17 no.3
• /
• pp.203-210
• /
• 2016

Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.10
• /
• pp.1193-1201
• /
• 1988

In this paper, we describe the syntactic and semantic parsing methods which use the case frames. The case structures based on obligatory cases of verbs. And, we use a small set of partial-garammar rules based on simple sentence to represent such case structures. Also, we enhance the efficiency by constructing independent procedure for particle classification and ambiguity resolution of major particle considering the importance of Japanese particle process in the generation. And we construct the generation table considering the combination possibility between the verbs and auxiliary verbs for processing the termination phrase. Therefore we can generate more natural translated sentence according to unique decision with information of syntactic analysis and simplify the generating process.

• Journal of the Korean Society of Earth Science Education
• /
• v.9 no.1
• /
• pp.65-87
• /
• 2016

The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.