• Journal of information and communication convergence engineering
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• v.13 no.1
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• pp.42-49
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• 2015

In laser pointer interaction systems, laser spot detection is one of the most important technologies, and most of the challenges in this area are related to the varying backgrounds, and the real-time performance of the interaction system. In this paper, we present a robust dictionary construction and update algorithm based on a sparse model of background subtraction. In order to control dynamic backgrounds, first, we determine whether there is a change in the backgrounds; if this is true, the new background can be directly added to the dictionary configurations; otherwise, we run an online cumulative average on the backgrounds to update the dictionary. The proposed dictionary construction and update algorithm for laser spot detection, is robust to the varying backgrounds and noises, and can be implemented in real time. A large number of experimental results have confirmed the superior performance of the proposed method in terms of the detection error and real-time implementation.

• Journal of Korean Library and Information Science Society
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• v.44 no.4
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• pp.233-254
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• 2013

Collecting terms in thesaurus construction work is the most difficult. A dictionary is thesaurus can be used as an excellent term acquisition. Reflect faithfully the provisions of Korean literary "Standard Korean Dictionary" is a standard dictionary of the Korea. The "Standard Korean Dictionary" is simply the definition of entry, as well as a wide range of information about the term because it contains a systematic, it can be used to build a thesaurus. In this study, the "Standard Korean Dictionary" has the relevant information using a variety of terms, it is defined as the thesaurus term relationship. In addition, the separation of the term, equal relationships and hierarchical set of relationships, the use of qualifiers, North Korean issues, the issue presented in thesaurus construction, and suggest ways to solve the problem.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.420-428
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• 2012

To improve the efficiency of business, it is important to standardize the meaning of terminology. And then, terminology dictionaries have been actively being built and used in various fields. In defense area, the publication of defense terminology dictionary is useful for information exchange of each army and distribution of standardized terminology. Defense agency for technology and quality(DTaQ) publishes terminology dictionary of defense science and technology on a three-year cycle. DTaQ tries to standardize the construction process of terminology dictionary and improve service efficiency by using terminology dictionary in defense area. This proposed method is based on the result of previous study about standardization of terminology dictionary. We suggest the practical steps including terminology dictionary constructing process, composition and role of organization, definition of headword, selection of target documents to be extracted terminology candidate, terminology extraction, generation of terminology candidate group, workbench registration, construction and validation of terminology dictionary. Thesaurus and workbench are developed to use and support terminology dictionary effectively.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.27-33
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• 2008

In this paper, we propose a method of automatically constructing a dictionary by extracting unknown words from given eojeols in order to improve the performance of a Korean morphological analyzer. The proposed method is composed of a dictionary construction phase based on full text analysis and a dictionary construction phase based on web document frequency. The first phase recognizes unknown words from strings repeatedly occurred in a given full text while the second phase recognizes unknown words based on frequency of retrieving each string, once occurred in the text, from web documents. Experimental results show that the proposed method improves 32.39% recall by utilizing web document frequency compared with a previous method.

• Speech Sciences
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• v.8 no.1
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• pp.33-52
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• 2001

A bilingual sound dictionary in Korean and English has been created for a broad range of sound reference to cross-linguistic, dialectal, native language (L1)-transferred biological and allophonic variations. The paper demonstrates that the pronunciation dictionary of the lexicon is inadequate for sound reference due to the preponderance of unmarked sounds. The audio registry consists of the three-way comparison of 1) English speech from native English speakers, 2) Korean speech from Korean speakers, and 3) English speech from Korean speakers. Several sub-dictionaries have been created as the foundation research for independent development. They are 1) a pronunciation dictionary of the Korean lexicon in a keyboard-compatible phonetic transcription, 2) a sound dictionary of L1-interfered language, and 3) an audible dictionary of Korean sounds. The dictionary was designed to facilitate the exchange of the speech signal and its corresponding text data on various media particularly on CD-ROM. The methodology and findings of the construction are discussed.

• Structural Engineering and Mechanics
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• v.91 no.2
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• pp.227-238
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• 2024

Sparse regularization methods have proven effective in addressing the ill-posed equations encountered in moving force identification (MFI). However, the complexity of vehicle loads is often ignored in existing studies aiming at enhancing MFI accuracy. To tackle this issue, a double 𝑙₁ regularization method is proposed for MFI based on a response spectrum-based weighted dictionary in this study. Firstly, the relationship between vehicle-induced responses and moving vehicle loads (MVL) is established. The structural responses are then expanded in the frequency domain to obtain the prior knowledge related to MVL and to further construct a response spectrum-based weighted dictionary for MFI with a higher accuracy. Secondly, with the utilization of this weighted dictionary, a double 𝑙₁ regularization framework is presented for identifying the static and dynamic components of MVL by the alternating direction method of multipliers (ADMM) method successively. To assess the performance of the proposed method, two different types of MVL, such as composed of trigonometric functions and driven from a 1/4 bridge-vehicle model, are adopted to conduct numerical simulations. Furthermore, a series of MFI experimental verifications are carried out in laboratory. The results shows that the proposed method's higher accuracy and strong robustness to noises compared with other traditional regularization methods.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.841-844
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• 1998

Korean Text to Sign Language Traslator could be applied to learn letters for both the deaf and hard-of-hearing people, and to have a conversation with normal people. This paper describes some useful dictionaries for developing korean text to sign language translator; Base sign language dictionary, Compound sign language dictionary, and Resemble sign language dictionary. As korean sign language is composed entirely of about 6,000 words, the additional dictionaries are required for matching them to korean written language. We design base sign language dictionary which was composed of basic symbols and moving picture of korean sign language, and propose the definition of compound isng language dictionary which was composed of symbols of base sing language. In addition, resemble sign language dictionary offer sign symbols and letters which is used same meaning in conversation. By using these methods, we could search quickly sign language during korean text to sign language translating process, and save storage space. We could also solve the lack of sign language words by using them, which are appeared on translating process.

• Language and Information
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• v.9 no.1
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• pp.19-34
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• 2005

Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. However, ontology construction requires vast amount of data collection and arduous efforts in processing these un-structured data. This study proposed a methodology to automatically construct and generate ontologies from Sejong Electronic Dictionary. As Sejong Electronic Dictionary is structured in XML format, it can be processed automatically by computer programmed tools into an OWL(Web Ontology Language)-based ontologies as specified in W3C . This paper presents the process and concrete application of this methodology.

• Language and Information
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• v.6 no.2
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• pp.33-55
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• 2002

This research aims at transforming the definition tort of an English-English-Korean Dictionary (EEKD) which is encoded in EST files for the purpose of publishing into a structured format for Lexical Data Base (LDB). The construction of LDB is very time-consuming and expensive work. In order to save time and efforts in building new lexical information, the present study tries to extract useful linguistic information from an existing printed dictionary. In this paper, the process of extraction and structuring of lexical information from a printed dictionary (EEKD) as a lexical resource is described. The extracted information is represented in XML format, which can be transformed into another representation for different application requirements.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.103-110
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• 2015

Sentiment lexicon is an essential element for expressing sentiment on a text or recognizing sentiment from a text. We propose a graph-based semi-supervised learning method to construct a sentiment dictionary as sentiment lexicon set. In particular, we focus on the construction of domain-specific sentiment dictionary. The proposed method makes up a graph according to lexicons and proximity among lexicons, and sentiments of some lexicons which already know their sentiment values are propagated throughout all of the lexicons on the graph. There are two typical types of the sentiment lexicon, sentiment words and sentiment phrase, and we construct a sentiment dictionary by creating each graph of them and infer sentiment of all sentiment lexicons. In order to verify our proposed method, we constructed a sentiment dictionary specific to the movie domain, and conducted sentiment classification experiments with it. As a result, it have been shown that the classification performance using the sentiment dictionary is better than the other using typical general-purpose sentiment dictionary.