• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.371-398
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• 2007

This study examined effects of word frequency and semantic transparency on decomposition processes of compound nouns by semantic priming task and repetition priming task. In Experiment 1, it was investigated that decomposition process depended on word frequency of compound noun. Semantic priming effects were found In the compound noun's associate rendition consistently, and repetition priming effects were found in the whole rendition as well as in the part condition irrespective of word frequency and SOA. These results implied that compound noun was processed through decomposition process path and direct access path. In Experiment 2, Effects of semantic transparency on decomposition processes of compound nouns were examined. Semantic priming effects were found when compound nouns' associates were presented as primes irrespective of semantic transparency and SOA, and results were the same as experiment 1b in repetition priming task. Results of experiment 1 and 2 implies that compound nouns are interpreted by interactive activation processes of attributes activated by decomposition path and direct access path.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.107-113
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• 2017

Most of online bookstores are providing a user with the bibliographic book information rather than the concrete information such as thematic words and atmosphere. Especially, thematic words help a user to understand books and cast a wide net. In this paper, we propose an efficient extraction method of thematic words from book text by applying the compound noun and noun phrase synthetic method. The compound nouns represent the characteristics of a book in more detail than single nouns. The proposed method extracts the thematic word from book text by recognizing two types of noun phrases, such as a single noun and a compound noun combined with single nouns. The recognized single nouns, compound nouns, and noun phrases are calculated through TF-IDF weights and extracted as main words. In addition, this paper suggests a method to calculate the frequency of subject, object, and other roles separately, not just the sum of the frequencies of all nouns in the TF-IDF calculation method. Experiments is carried out in the field of economic management, and thematic word extraction verification is conducted through survey and book search. Thus, 9 out of the 10 experimental results used in this study indicate that the thematic word extracted by the proposed method is more effective in understanding the content. Also, it is confirmed that the thematic word extracted by the proposed method has a better book search result.

• Korean Journal of Cognitive Science
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• v.17 no.1
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• pp.15-27
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• 2006

The effects of the number of Hangul syllable, the nunber/location of batchim in a Hangul word, and compound/noncompound Hangul word on memory span were examined. The results were that (1) the more syllables a word had, the lower us memory span was, (2) the more batchims a two-syllable word had, the lower its memory span was (Korean batchim effect on memory span), (3) noncompound word had higher memory span than compound word. The reading speed of above mentioned words was measured and the results were that (1) the more syllables a word had, the slower its reading speed was, (2) but the reading speed of a two-syllable word was forest when it had a batchim on second syllable than when it had no batchim or had a batchim on first syllable or batchims on both syllables (Korean ending batchim effect on reading speed), (3) noncompound word was read faster thu compound word. Korean ending batchim effect on reading speed was not compatible with the explanation by articulatory loop bur compatible with the explanation by visual cache where the orthographic information was represented. The results suggest that memory span was influenced nor only by phonological information but also by orthographic information.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.79-91
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• 2002

Structural analysis of compound words is necessary and an important process in natural language processing. Proposed here is a corpus- and statistics- based method for the structural analysis of compound words in Japanese. We determine the structure of a compound word by using Internet corpus and calculating the strength of word association among its constituent words. Experiments with 5, 6, 7, and 8 kanji compound words show that our method works well and its performance is better than those of other comparable studies.

• The Research Journal of the Costume Culture
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• v.7 no.2
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• pp.220-224
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• 1999

This study is concerned with the names of is sa mai(잇사매) and ham sa mai(함사매). Origins and meanings of these terms were traced and examined. Some significant findings can be summarized as follows : Korean word is sa mai(잇사매) was a compound word. Korean character is (잇) is derived from Chinese character i, and sa mai(사매) in Korean means sleeves 神 in Chinese character. The character ham in Ham sa mai(함사매) is its origin in Chinese : Korean character ham was Korean pronounciation of the Chinese character, han. ham sa mai is a compound word of ham(함) (Korean), (han ) (Chinese) and sa mai(사매) sleeves(Korean). Thus, first characters of is(잇) in is sa mai(잇사매) and ham(함) in ham sa mai(함사매) are originated from Chinese, where as the word sa mai in the end of is sa mai and ham sa mai is pure Korean. Both character i and ham(han, Chinese) in Chinese means a jaw. Thus, both is sa mai(잇사매) and ham sa mai(함사매) means “jawed sleeves”. That is long and wide round sleeves with narraw wrists.

• Lingua Humanitatis
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• v.2 no.1
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• pp.303-314
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• 2002

The main purpose of this paper is to show how Jespersen analyzed the date of English compound related with reduplication. Especially dealing with the compound words he classified the examples related with reduplication as a separate part and attempted to account for the patters based on the structure of the first syllable constituting the initial part of the second element in a compound word. 1 tried to explain the peculiar shape of the reduplicational pattern in English based on the Optimality Theory, especially the method of 'melodic overwriting' of McCarthy(1997). According to the analysis the initial part of the second element of a compound has to be stipulated before reduplication occurs. When the reduplicant has to be decided at the first syllable of the second element, the form which is stipulated to take the position comes to appear at the post instead of repeating the morphemic shape of the first syllable at the first element of the word.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.274-284
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• 2002

Word segmentation errors occurring in text preprocessing often insert incorrect words into recognition vocabulary and cause poor language models for Korean large vocabulary continuous speech recognition. We propose an automatic word segmentation algorithm using Markov chains and syllable-based n-gram language models in order to correct word segmentation error in teat corpora. We assume that a sentence is generated from a Markov chain. Spaces and non-space characters are generated on self-transitions and other transitions of the Markov chain, respectively Then word segmentation of the sentence is obtained by finding the maximum likelihood path using syllable n-gram scores. In experimental results, the algorithm showed 91.58% word accuracy and 96.69% syllable accuracy for word segmentation of 254 sentence newspaper columns without any spaces. The algorithm improved the word accuracy from 91.00% to 96.27% for word segmentation correction at line breaks and yielded the decomposition accuracy of 96.22% for compound-noun decomposition.

• MALSORI
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• no.42
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• pp.57-69
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• 2001

Syntactic ambiguity can be understood by context usually, especially in reading and writing. Because phonological structure including stress, intonation and phonological phenomena can be pronounced differently according to different syntactic structures, syntactic ambiguity can be solved by phonological structure in listening and speaking. The objectives of this study was to survey how Korean English teachers apply phonological structures in order to solve syntactic ambiguity. The results of this study is as follows: First, Korean English leachers applied Compound Stress Rules well, when the second word was not branched. But they did not apply Compound Stress Rules well, when the second word was branched. Second, several Korean English teachers did not apply Nuclear Stress Rules well. They usually put the strongest stress on the first word. Third Korean English teachers did not differentiate appropriate applying situation of palatalization. They applied palatalization at both the single and the separated Phonological Phrase. Fourth, Korean English teachers did not apply stress shifting when stress crash happened. Because they did not apply stress shifting, they put the strongest stress on inappropriate syllable.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1073-1089
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• 2006

The goal of Natural Language Processing(NLP) is to make a computer understand a natural language and to deliver the meanings of natural language to humans. Word sense Disambiguation(WSD is a very important technology to achieve the goal of NLP. In this paper, we describe a technology for automatic homonyms disambiguation using both Mutual Information(MI) and a Sense-Tagged Compound Noun Dictionary. Previous research work using word definitions in dictionary suffered from the problem of data sparseness because of the use of exact word matching. Our work overcomes this problem by using MI which is an association measure between words. To reflect language features, the rate of word-pairs with MI values, sense frequency and site of word definitions are used as weights in our system. We constructed a Sense-Tagged Compound Noun Dictionary for high frequency compound nouns and used it to resolve homonym sense disambiguation. Experimental data for testing and evaluating our system is constructed from QA(Question Answering) test data which consisted of about 200 query sentences and answer paragraphs. We performed 4 types of experiments. In case of being used only MI, the result of experiment showed a precision of 65.06%. When we used the weighted values, we achieved a precision of 85.35% and when we used the Sense-Tagged Compound Noun Dictionary, we achieved a precision of 88.82%, respectively.

• ETRI Journal
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• v.32 no.5
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• pp.740-749
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• 2010

In a machine translation system, word sense disambiguation has an essential role in the proper translation of words when the target word can be translated differently depending on the context. Previous research on sense identification has mostly focused on adjacent words as context information. Therefore, in the case of nominal compounds, sense tagging of unit nouns mainly depended on other nouns surrounding the target word. In this paper, we present a practical method for the sense tagging of Korean unit nouns in a nominal compound. To overcome the weakness of traditional methods regarding the data sparseness problem, the proposed method adopts complement-predicate relation knowledge that was constructed for machine translation systems. Our method is based on a sentential form recovery technique, which recognizes grammatical relationships between unit nouns. This technique makes use of the characteristics of Korean predicative nouns. To show that our method is effective on text in general domains, the experiments were performed on a test set randomly extracted from article titles in various newspaper sections.