• Korean Linguistics
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• v.80
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• pp.151-175
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• 2018

This paper proposed a method of semantic recognition to improve the extraction of correct answers of the Q&A system through machine learning. For this purpose, the semantic recognition method is described based on the distribution of predicative nouns. Predicative noun vocabularies and sentences were collected from Wikipedia documents. The predicative nouns are typed by analyzing the environment in which the predicative nouns appear in sentences. This paper proposes a semantic recognition method of predicative nouns to which rules can be applied. In Chapter 2, previous studies on predicative nouns were reviewed. Chapter 3 explains how predicative nouns are distributed. In this paper, every predicative nouns that can not be processed by rules are excluded, therefore, the predicative nouns noun forms combined with the case marker '의' were excluded. In Chapter 4, we extracted 728 sentences composed of 10,575 words from Wikipedia. A semantic analysis engine tool of ETRI was used and presented a predicative nouns noun that can be handled semantic recognition language.

• 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.

• Journal of the Korean Institute of Rural Architecture
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• v.5 no.3
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• pp.34-43
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• 2003

This study attempts to understanding of outer space elements in a rural house through an analysis nouns for function definition phase in design value engineering. To choose main check objects, this study examines requests by rural dwellers and analyze function definition in design value engineering. The rural dwellers prefers that barrier free design, outdoor working space and security of calamity. Each selected elements are classified the nouns into a main noun by analysis function definition nouns at design VE phase. The nouns are reclassified into the main nouns as a distance, a space, and a form.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.103-112
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• 2002

This paper aims to give an explanation of the combination of certain nouns and the verb ha-'do'. Although the verb ha-'do'normally takes an event type argument, it takes some substantival nouns such as paiolin 'violin', umsikcem 'restaurant', and so on. A substantival noun undergoes type shifting, because the governing verb ha-'do'coerces an entity type noun to an event reading, taking missing information from the qualia of the entity type noun. In addition, some nouns like ppallay 'laundry'are dot objects. The verb laking a dot objects selects a proper type between multiple subtypes of the dot object. Type pumping operation makes that selection possible.

• 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.

• Korean Journal of Cognitive Science
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• v.17 no.2
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• pp.119-138
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• 2006

It is widely known that chunking is beneficial to syntactic analysis. This paper introduces a method of chunking thai is useful for structural analysis of sentences in Korean. Dependent nouns in Korean usually tend to make sentences complex and long. By performing chunking operations related with dependent nouns, it is possible to reduce sentence complexity and thus make syntactic analysis easier. With this aim in mind we investigated techniques for chunking related with dependent nouns. We proposed a variety of chunking schemes according to the types of dependent nouns. The experiments showed that carrying out chunking leads to significant improvement of performance in syntactic analysis for Korean.

• 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.

• Journal of the Society of Disaster Information
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• v.7 no.2
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• pp.140-150
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• 2011

Life Environment is rapidly changing and large scale disasters are increasing from the global warming. Although the disaster repair resources are deployed to the disaster fields, the prevention of the disasters is the most effective countermeasures. the disaster sign data is based on the rule of Heinrich. Automatic extraction of the disaster sign data from the web is the focused issues in this paper. We defined the automatic extraction processes and applied information, such as accident nouns, disaster filtering nouns, disaster sign nouns and rules. Using the processes, we implemented the disaster sign data management system. In the future, the applied information must be continuously updated, because the information is only the extracted and analytic result from the some disaster data.