• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.23-31
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• 2004

Latent Semantic Analysis (LSA Landauer ＆ Dumais, 1997) is a technique to represent the meanings of words using co-occurrence information of words appearing in he same context, which is usually a sentence or a document. In LSA, a word is represented as a point in multidimensional space where each axis represents a context, and a word's meaning is determined by its frequency in each context. The space is reduced by singular value decomposition (SVD). The present study elaborates upon LSA for use of representation of ambiguous words. The proposed LSA applies rotation of axes in the document space which makes possible to interpret the meaning of un. A simulation study was conducted to illustrate the performance of LSA in representation of ambiguous words. In the simulation, first, the texts which contain an ambiguous word were extracted and LSA with rotation was performed. By comparing loading matrix, we categorized the texts according to meanings. The first meaning of an ambiguous wold was represented by LSA with the matrix excluding the vectors for the other meaning. The other meanings were also represented in the same way. The simulation showed that this way of representation of an ambiguous word can identify the meanings of the word. This result suggest that LSA with axis rotation can be applied to representation of ambiguous words. We discussed that the use of rotation makes it possible to represent multiple meanings of ambiguous words, and this technique can be applied in the area of web searching.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.93-108
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• 2011

We propose a extended vector space model by using ambiguous words and disambiguous words to improve the result of a Korean document classification method. In this paper we study the precision enhancement of vector space model and we propose a new axis that represents a weight value. Conventional classification methods without the weight value had some problems in vector comparison. We define a word which has same axis of the weight value as ambiguous word after calculating a mutual information value between a term and its classification field. We define a word which is disambiguous with ambiguous meaning as disambiguous word. We decide the strengthness of a disambiguous word among several words which is occurring ambiguous word and a same document. Finally, we proposed a new classification method based on extension of vector dimension with ambiguous and disambiguous words.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.563-568
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• 2016

The word sense disambiguation problem is to find the correct sense of an ambiguous word having multiple senses in a dictionary in a sentence. We regard this problem as a multi-class classification problem and classify the ambiguous word by using Support Vector Machines. Context words of the ambiguous word, which are extracted from Sejong sense tagged corpus, are represented to two kinds of vector space. One vector space is composed of context words vectors having binary weights. The other vector space has vectors where the context words are mapped by word embedding model. After experiments, we acquired accuracy of 87.0% with context word vectors and 86.0% with word embedding model.

• Phonetics and Speech Sciences
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• v.1 no.1
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• pp.87-91
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• 2009

The purpose of this study was to examine the characteristics of prosody of utterance of ambiguous sentences in patients with neurogenic communication disorders. Ambiguous words on which prosody may have an impact were used to investigate this matter. The characteristics of tone duration, pitch and intensity were analyzed to examine the characteristics of prosody in patients with lesions in the left or right hemisphere and normal controls. The whole process was recorded using a Praat 4.3.14 and for statistical analyses, two-way Anova and multiple comparative analyses were carried out using SPSS10.0 for Windows. The conclusions of this study are as follows: The length of vowel in homograph in Korean was different depending on the meaning and the duration of vowel was the longest in patients with lesions in the left hemisphere. There was agreed that they had problem of timing of prosody(Danly & Shapiro, 1982). On the other hand, there found that patients with lesions in the right hemisphere had deficiency of changeability in pitch. Among various acoustic parameters, this study focused on the duration which are closely related to suprasegmental characteristics of prosody. More acoustic parameters should be taken into account in future studies.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.427-431
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• 2007

In this paper we describe a Korean part-of-speech tagging approach using resolution rules for individual ambiguous word and statistical information. Our tagging approach resolves lexical ambiguities by common rules, rules for individual ambiguous word, and statistical approach. Common rules are ones for idioms and phrases of common use including phrases composed of main and auxiliary verbs. We built resolution rules for each word which has several distinct morphological analysis results to enhance tagging accuracy. Each rule may have morphemes, morphological tags, and/or word senses of not only an ambiguous word itself but also words around it. Statistical approach based on HMM is then applied for ambiguous words which are not resolved by rules. Experiment shows that the part-of-speech tagging approach has high accuracy and broad coverage.

• Korean Journal of Cognitive Science
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• v.20 no.3
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• pp.309-333
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• 2009

Two experiments were conducted to examine the role of Kulja and morpheme in processing two-syllable Sino-Korean words. In Experiment 1, the effects of morphemic frequency were not significant at the initial and final positions of a word while Kulja frequency and Kulja-morpheme correspondence at both positions in a word had a significant impact on the processing of nonwords. Lexical decision times were longer for nonwords with high frequency Kulja and for nonwords with ambiguous Kulja-morpheme correspondence whose Kulja can go with many different morphemes. In Experiment 2 Kulja-morpheme correspondence was examined for words as well as nonwords. Lexical decisions were slower for stimuli with ambiguous Kulja-morpheme correspondence. The effect was more stable for nonwords, which replicated the result of Experiment 1. In sum, the results of this study suggest that words with ambiguous Kulja-morpheme correspondence activate many different morphemes and competition among these morphemic candidates slows down the lexical selection process. Kulja frequency, Kulja neighborhood, morphemic frequency, morphological neighborhood, and Kulja-morpheme correspondence in Korean word recognition were also discussed.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• Journal of Information Technology Applications and Management
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• v.9 no.2
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• pp.71-80
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• 2002

Automatic language translation has greatly advanced due to the increased user needs and Information retrieval in WWW. This paper utilizes the integrated knowledge bases of noun and verb networks for automatic translation of ambiguous words in the Korean sentences, through the selectional restriction relation in the sentences. And this paper presents the method to verify validity of Korean noun semantic networks that are used for the construction of the selectional restriction relation by applying the networks to the syntactic and semantic properties Integration of Korean Noun Networks into the SENKOV system will provide the accurate and efficient knowledge bases for the semantic analysis of Korean NLP.

• Speech Sciences
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• v.8 no.4
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• pp.275-288
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• 2001

The sentences with the same surface word order may be realized with the pragmatically different meanings, depending on the contexts under which they could appear. Semantically, their meaning differences have been explained in terms of the different information structures (Steedman 2000), whereas prosodically, they can be explained in terms of the different compositions of intonational components which make their own semantic contributions (Pierrehumbert and Hirschberg 1990). In other words, the different intonation realizations of the sentences with the same word order reflect the different information structures. In this paper, we investigate the relationship between the information structure and the intonational meaning by way of analysing the production of the sentences with ambiguous scopes of the English focus particle 'only'. In contrast to the previous quantitative approaches to the scopes of the focus particle 'only', two independent levels of information structure (Steedman 2000)-theme/rheme, and focus/ background-make it possible to consistently explain the intonational phenomena.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.129-139
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• 1994

This paper presents a morphological analysis method for the Korean language. The characteristics and adjacency information of the words can be obtained from sentences in a large corpus. Generally a word can be analyzed to a result by applying the adjacency attributes and rules. However, we have to choose one from the several results for the ambiguous words. The collected morpheme's adjacency attributes and relations with neighbor words are recorded in a well designed dictionaries. With this information, abbreviated words as well as ambiguous words can be almost analyzed successfully. Efficiency of morphological analyzer depends on the information in the dictionaries. A morpheme dictionary and a phrase dictionary have been designed with lexical database, and necessary information extracted from the corpus is stored in the dictionaries.