• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.95-102
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• 2004

This paper proposes a method of segmenting compound nouns which include unregistered nouns into a correct combination of unit nouns using characteristics of person's names, loanwords, and location names. Korean person's name is generally composed of 3 syllables, only relatively small number of syllables is used as last names, and the second and the third syllables combination is somewhat restrictive. Also many person's names appear with clue words in compound nouns. Most loanwords have one or more syllables which cannot appear in Korean words, or have sequences of syllables different from usual Korean words. Location names are generally used with clue words designating districts in compound nouns. Use of above characteristics to analyze compound nouns not only makes segmentation more accurate, helps natural language systems use semantic categories of those unregistered nouns. Experimental results show that the precision of our method is approximately 98% on average. The precision of human names and loanwords recognition is about 94% and about 92% respectively.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.151-159
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• 2006

The ratio of a segmentation algorithm of compound nouns causes an effect a lot in nouns which are not in the dictionary. The structure of Korean compound nouns are mostly derived from the Chinese characters and it includes some preference ratio. So it will be able to use segmentation rule of compound nouns. This paper suggests a segmentation algorithm using some preference ratio of Korean compound nouns which are not in the dictionary. The experiment resulted in getting 88.49% of correct segmentation and showed effective result from the comparative experimentation with other algorithm.

• Smart Media Journal
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• v.8 no.2
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• pp.74-79
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• 2019

Traditional compound noun decomposition algorithms often face challenges of decomposing compound nouns into separated nouns when unregistered unit noun is included. It is very difficult for those traditional approach to handle such issues because it is impossible to register all existing unit nouns into the dictionary such as proper nouns, coined words, and foreign words in advance. In this paper, in order to solve this problem, compound noun decomposition problem is defined as tag sequence labeling problem and compound noun decomposition method to use syllable unit embedding and deep learning technique is proposed. To recognize unregistered unit nouns without constructing unit noun dictionary, compound nouns are decomposed into unit nouns by using LSTM and linear-chain CRF expressing each syllable that constitutes a compound noun in the continuous vector space.

• Speech Sciences
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• v.12 no.4
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• pp.153-166
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• 2005

This paper attempts to examine the accent implementation and perception of noun phrases and compound nouns in English sentences, arguing that primary stress of noun phrase and compound noun is realized in relative prominence in intonation. The production test examines how the stress patterns of the noun phrases and compound nouns are realized in intonation of the English native speakers' utterances. The perception test investigates English and Korean listeners' comprehension of the intonation of the noun phrases and compound nouns. And the results of this experimental study show that speakers and listeners produce and perceive the primary stress as a relatively prominent accent even if in contrast of English listeners, Korean learners have difficulty in using the cue of pitch accent location and figuring out compound nouns and noun phrases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.306-310
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• 2004

This paper suggests a reverse segmentation algorithm using affix information and some preference pattern information of Korean compound nouns. The structure of Korean compound nouns is mostly derived from Chinese characters, and it includes some preference patterns utilized as a segmentation rule in this paper. To evaluate the accuracy of the proposed algorithm, an experiment was performed with 36,061 compound nouns. The experiment resulted in getting 99.3% of correct segmentation and showed excellent satisfactory results from the comparative experimentation with other algorithms. Especially, most of the four-syllable or five-syllable compound nouns were successfully segmented without fail.

• MALSORI
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• no.42
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• pp.25-36
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• 2001

Stress assignment has been much discussed in the literature on English compound nouns. The general view of the stress pattern of English compound nouns is that a main stress falls on the first element and a secondary stress on the second element; however, a stress pattern is often employed that provides counterevidence to the traditional pedagogical approach. A new idea is suggested by Ladd(1984) that 'compound stress represents the deaccenting of the head of the compound.' Recent studies show that initial stressing does not indicate compounds and syntactic phrases are not always characterized by final stressing. In his pilot test Pennanen comments on the frequent variation of stress patterns on individual items, on the basis of which Bauer confirms Pennanen's results with different informants. This paper is an attempt to justify Bauer's analysis with the same data as Bauer's and different subjects. It turns out that the competences of native-speaker informants do not rovide clear-cut answers. Some factors should be taken into account in assigning appropirate stress to compound nouns.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.418-426
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• 2004

This paper suggests a reverse segmentation Algorithm using affix information and some preference pattern information of Korean compound nouns. The structure of Korean compound nouns are mostly derived from the Chinese characters and it includes some preference patterns, which are going to be utilized as a segmentation rule in this paper. To evaluate the accuracy of the proposed algorithm, an experiment was performed with 36061 compound nouns. The experiment resulted in getting 99.3% of correct segmentation and showed excellent satisfactory result from the comparative experimentation with other algorithm, especially most of the four or five-syllable compound nouns were successfully segmented without fail.

• Korean Journal of Cognitive Science
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• v.6 no.3
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• pp.65-81
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• 1995

Compound nouns as a composition of multiple nouns exhibit diverse occurence patterns in the texts and have varying degree of meaning coherence.The problem of compound nouns in information retrieval is to find a method to represent and identify the compositive patterns of each words.This paper explains how the cooccurrence patterns are related with the meaning of each compound noun and the information of such relations that can be mechanically acquired from texts is used in ranking the candidated documents for a given query.The main theme of the paper is that compound nouns can be categorized according to their occurrence patterns of simple nouns and these occurrence patterns can be formalized by statistical analysis without large dictionary or complex compositive rules.Our suggested model achieved about 7.75% improvement over the best precision of the other methods at each recall measurements on Korean test collection.

• 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.