• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.191-197
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• 2019

Morphological analysis is used for searching sentences and understanding context. As most morpheme analysis methods are based on predefined dictionaries, the problem of a target word not being registered in the given morpheme dictionary, the so-called unregistered word problem, can be a major cause of reduced performance. The current practical solution of such unregistered word problem is to add them by hand-write into the given dictionary. This method is a limitation that restricts the scalability and expandability of dictionaries. In order to overcome this limitation, we propose a novel method to automatically expand a dictionary by means of use-case analysis, which checks the validity of the unregistered word by exploring the use-cases through web crawling. The results show that the proposed method is a feasible one in terms of the accuracy of the validation process, the expandability of the dictionary and, after registration, the fast extraction time of morphemes.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.45-53
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• 2003

The significances of this paper are of two points. One is that this research develops the query expansion search by adding the related terms based on the dictionary to the original query terms. This method shortens the process of the conventional model of query expansion utilizing the feedback data of the search. The other is that this research tries to find out the optimal point of precisions and recalls by differentiating the weight ratio between original quay and additional terms. This method shows that the efficiency and precision of query expansion search increase.

• Journal of IKEEE
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• v.13 no.2
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• pp.241-247
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• 2009

This paper suggests the expansion methods of semantic dictionary, taking Korean semantic features account. These methods will be used to extract a practical topic word in the automatic summarization. The first is the method which is constructed the synonym dictionary for improving the performance of semantic-marker analysis. The second is the method which is extracted the probabilistic information from the subcategorization dictionary for resolving the syntactic and semantic ambiguity. The third is the method which is predicted the subcategorization patterns of the unregistered predicate, for the resolution of an affix-derived predicate.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.35-42
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• 2013

Developing English-Korean machine translation system requires the construction of information about the languages, and the amount of information in English-Korean transfer dictionary is especially critical to the translation quality. Newly created words are out-of-vocabulary words and they appear as they are in the translated sentence, which decreases the translation quality. Also, compound nouns make lexical and syntactic analysis complex and it is difficult to accurately translate compound nouns due to the lack of information in the transfer dictionary. In order to improve the translation quality of English-Korean machine translation, we must continuously expand the information of the English-Korean transfer dictionary by collecting the out-of-vocabulary words and the compound nouns frequently used. This paper proposes a method for expanding of the transfer dictionary, which consists of constructing corpus from internet newspapers, extracting the words which are not in the existing dictionary and the frequently used compound nouns, attaching meaning to the extracted words, and integrating with the transfer dictionary. We also develop the tool supporting the expansion of the transfer dictionary. The expansion of the dictionary information is critical to improving the machine translation system but requires much human efforts. The developed tool can be useful for continuously expanding the transfer dictionary, and so it is expected to contribute to enhancing the translation quality.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.278-281
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• 2000

Matching pursuit algorithm is a signal expansion technique whose efficiency for motion compensated residual image has already been demonstrated in the MPEG-4 framework. However, one of the practical concerns related to applying matching pursuit algorithm to real-time scalable video coding is its massive computation required for finding dictionary elements. In this respective, this paper proposes a fast algorithm, which is composed of three sub-methods. The first method utilizes the property of symmetry in 1-D dictionary element and the second uses mathematical elimination of inner product calculation in advance, and the last one uses frequency property of 2-D dictionary. Experimental results show that our algorithm needs about 30% computational load compared to the conventional fast algorithm using separable property of 2-D gabor dictionary with negligible quality degradation.

• Journal of Digital Convergence
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• v.13 no.5
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• pp.187-194
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• 2015

Various linguistic knowledge resources are required in order that machine can understand diverse variation in natural languages. This paper aims to devise an automatic construction method of linguistic resources by reflecting characteristics of online contents toward continuous expansion. Especially we focused to build NE(Named-Entity) dictionary because the applicability of NEs is very high in linguistic analysis processes. Based on the investigation on Korean Wikipedia, we suggested an efficient construction method of NE dictionary using the syntactic patterns and structural features such as metadatas.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.217-225
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• 2019

National research and development(R&D) information is information generated in the process of performing R&D based on programs and projects issued by national government departments, and includes information from various research fields as ordered by various departments. Therefore, for efficient R&D information retrieval, it is necessary to build a national R&D terminology dictionary that can reflect the characteristics of such national R&D information. In this study, we propose a method for constructing a national R&D terminology dictionary by applying the classification of science and technology standards used to specify the research field in national R&D information. We will discuss the structural characteristics of national R&D project information and the usefulness of the project keyword, and explain the status of national R&D information by the National Standard Science and Technology Classification(NSSTC) Codes and the characteristics of the national R&D terminologies. Based on this, a method for building a national R&D terminology dictionary is defined in terms of the type and structure of the terminology dictionary, preliminary construction procedures, and refining rules. The national R&D terminology dictionary built on the basis of this study can be used in various ways such as expansion of search terms using Korean-English equivalent words and synonyms when searching national R&D information, clarifying the scope of search using NSSTC, and providing user convenience functions using term explanation information.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.28-45
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• 2023

Although we have entered the era of digital transformation, there is currently no system that efficiently collects, manages, integrates, and services a large number of archaeological digital source materials produced as a result of cultural relics research, i.e., an intelligent integrated management and service platform for archaeological academic information. In this regard, the need to build a digital dictionary of Korean archaeology was confirmed by examining the problem of the Digital Encyclopedia of Korean Archaeology, which is currently available in PDF format on the web, the current status of the publication and use of the Dictionary of Korean Archaeology, and the cases of building digital platforms at home and abroad. Therefore, this paper aims to suggest a general direction for creating a digital encyclopedia of Korean archaeology based on the Dictionary of Korean Archaeology, which includes quality knowledge information, to reconsider the accessibility of archaeological data in conformity with data access limitations. The application of the series Dictionary of Korean Archaeology, published since 2001, and the necessity for digital transformation were examined, as well as the application of data from the archaeological data archiving platforms of Europe, the USA, Japan, and cases of establishing platforms corresponding to specialized encyclopedias from Korea. Based on these, a three-step implementation plan and detailed projects were suggested to create the Digital Encyclopedia of Korean Archaeology. Through this, we proposed the design of metadata for computerized records and the expansion to semantic (meaning-based) data that gives and shows the relationship information between the produced metadata as the implementation tasks to build the Digital Dictionary of Korean Archaeology. It is hoped that such research will help create an integrated intelligent management and service platform for archaeology, raise awareness, and provide a better understanding of Korean archaeology to the general public.

• Korean Linguistics
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• v.78
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• pp.31-54
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• 2018

'맞다(right)', which is inversely related to 'teullida', has a synonymic relationship with '같다(same)' depending on the sense. Naturally, the '같다' is usually inversely related to '다르다(be different)' as symmetry verb. The meaning of '다르다' is 'teullida' and there is a close meaning relationship network in the network of words. In other words, the process acting as a driver of the expansion of meanings based on the antonym-relation of (1)'틀리다${\leftrightarrow}$맞다', and the s?ynonym-relation of (2)'맞다 = 같다' forms a network, and the relation between them and the opposite semantics is (3)'같다=맞다${\leftrightarrow}$다르다'. And many of today's speakers speak (4)'teullida' of [difference]. Therefore, after the application of the synonymic analogy, eventually, the antonymic analogy is formed, and the word formed is 'teullida' of [difference]. This, of course, forms another type of enlargement of the meaning.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.93-98
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• 2010

In this paper, we introduce a system that summarizes product evaluation through linguistic analysis to effectively utilize explosively increasing product reviews. Our system analyzes polarities of product reviews by product features, based on which customers evaluate each product like 'design' and 'material' for a skirt product category. The system shows to customers a graph as a review summary that represents percentages of positive and negative reviews. We build an opinion word dictionary for each product feature through context based automatic expansion with small seed words, and judge polarity of reviews by product features with the extracted dictionary. In experiment using product reviews from online shopping malls, our system shows average accuracy of 69.8% in extracting judgemental word dictionary and 81.8% in polarity resolution for each sentence.