• Journal of Information Management
• /
• v.37 no.4
• /
• pp.25-47
• /
• 2006

A terminology system capable of providing interpretations and classification information on a multilingual science and technology(S&T) terminology is essential to establish an integrated search environment for multilingual S&T information systems. This paper aims to build a base system to manage an integrated information system for multilingual S&T terminology search. It introduces a method to build a search system for S&T terminologies internally linked through the multilingual semantic network and a search technique on the multiple linked nodes. In order to provide a foundation for further analysis researches, it also attempts to suggest a basic approach to interpret terminology clusters generated with those two search methods.

• Journal of the Korean Society for information Management
• /
• v.19 no.1
• /
• pp.135-161
• /
• 2002

This study presents a multilingual integrated ontological approach that enables linking classification systems. thesauri. and terminology databases in science and technology for more effective indexing and information retrieval online. In this integrated system, we designed a thesaurus model with concept as a unit and designated essential data elements for a terminology database on the basis of ISO 12620 standard. The classification system for science and technology adopted in this study provides subject access channels from other existing classification systems through its mapping table. A prototype system was implemented with the field of nuclear energy as an application area.

• Journal of Intelligence and Information Systems
• /
• v.10 no.2
• /
• pp.1-13
• /
• 2004

This paper presents a method for the multilingual product retrieval agent through XML and the semantic networks in e-commerce. Retrieval for products is an important process, since it represents interfaces of the customer contact to the e-commerce. Keyword-based retrieval is efficient as long as the product information is structured and organized. But when the product information is expressed across many online shopping malls, especially when it is expressed in different languages with cultural backgrounds, buyers' product retrieval needs language translation with ambiguities resolved in a specific context. This paper presents a RDF modeling case that resolves semantic problems in the representation of product information and across the boundaries of language domains. With adoption of UNSPSC code system, this paper designs and implements an architecture for the multilingual product retrieval agents. The architecture is based on the central repository model of product catalog management with distributed updating processes. It also includes the perspectives of buyers and suppliers. And the consistency and version management of product information are controlled by UNSPSC code system. The multilingual product names are resolved by semantic networks, thesaurus and ontology dictionary for product names.

• Journal of Information Management
• /
• v.26 no.2
• /
• pp.61-79
• /
• 1995

The purpose of this paper is to investigate search efficiency of controlled vocabulary versus uncontrolled vocabulary subject access in online catalog systems. The question of the effectiveness of controlled versus uncontrolled vocabulary in information retrieval has been raised in many literatures. A debate continues in the Library and Information Science Professions over the relative merit, appropriateness, and efficiency of uncontrolled vocabulary subject access in online catalog systems. Actually users used to combine uncontrolled vocabulary subject searching with controlled vocabulary subject searching. But the success of user's subject search depends on his choice of search terms. Also the technical developments that facilitate cooperation among information services in general make it increasingly possible for such cooperation to take place on an international level. In this study, several common types of vocabularies on online catalog systems are described and compared, especially usages of vocabularies in multilingual environment are analyzed.

• Journal of KIISE:Software and Applications
• /
• v.32 no.7
• /
• pp.636-649
• /
• 2005

Field-associated Terms itself have field Information. So, they determine field of document just like when human being perceives field. In case of Korean, we organized and experimented them by collecting approximately IS,999 document banks that are classified into 180 fields. We obtained high precision of extraction that 88,782 single field-associated terms are contracted into 8,405 ones thus recording compression rate as approximately 9$\%$ and recall as above 0.77 (average 0.85), precision as above 0.90 (average 0.94). By applying established field-associated terms to initial determination for document classification and comparing it with filed determination by human being, we got correct answers above approximately 90$\%$. We can use results of research as fundamental research for initial stage and apply it document retrieval between multilingual environment thus utilizing it as fundamental research for multilingual information retrieval.

• International Journal of Computer Science & Network Security
• /
• v.22 no.4
• /
• pp.183-192
• /
• 2022

The role that English currently plays is undeniable. It has become the most common means of communication among native speakers of several languages around the world. English penetrates into all areas of people's daily lives. In the field of Information Technology (IT), English has taken a dominant position, as many of the terms used on a daily basis are written in English. The purpose of the article is to analyze the linguistic features of anglicisms in the field of Information Technology. Methods. The research is based on systematic and comparative analysis, dialectical method, as well as methods of classification and generalization. Results. This study presents the results of compiling a multilingual glossary with anglicisms used in the GitHub and 3D Slicer fields. Despite the limited number of terms included in the glossary, the article provides a lot of evidence for the influence of the English language in the areas of Information Technology, GitHub and 3D Slicer under consideration. The types of anglicisms used in the 3D Slicer area seem to be more diverse than in the GitHub area. This study found that five European languages use language strategies to solve any communication problem. The multilingual glossary showed that in some cases there is a coexistence between Anglicism and the native term. In other cases, the English term is the only one used in different languages. There are cases when only the native language is used. Conclusions. This study is a useful tool that helps to improve the efficiency of communication between engineers and technicians who speak different native languages. The ultimate goal of this research will be to create a multilingual glossary that is still under development and is likely to cover other IT areas such as Python and VTK.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.5
• /
• pp.15-30
• /
• 2023

Recently, generative models based on the Transformer architecture, such as ChatGPT, have been gaining significant attention. The Transformer architecture has been applied to various neural network models, including Google's BERT(Bidirectional Encoder Representations from Transformers) sentence generation model. In this paper, a method is proposed to create a text binary classification model for determining whether a comment on Korean movie review is positive or negative. To accomplish this, a pre-trained multilingual BERT sentence generation model is fine-tuned and transfer learned using a new Korean training dataset. To achieve this, a pre-trained BERT-Base model for multilingual sentence generation with 104 languages, 12 layers, 768 hidden, 12 attention heads, and 110M parameters is used. To change the pre-trained BERT-Base model into a text classification model, the input and output layers were fine-tuned, resulting in the creation of a new model with 178 million parameters. Using the fine-tuned model, with a maximum word count of 128, a batch size of 16, and 5 epochs, transfer learning is conducted with 10,000 training data and 5,000 testing data. A text sentiment binary classification model for Korean movie review with an accuracy of 0.9582, a loss of 0.1177, and an F1 score of 0.81 has been created. As a result of performing transfer learning with a dataset five times larger, a model with an accuracy of 0.9562, a loss of 0.1202, and an F1 score of 0.86 has been generated.

• International Journal of Knowledge Content Development & Technology
• /
• v.7 no.4
• /
• pp.71-84
• /
• 2017

The paper discusses the nature of Knowledge Organization Systems (KOSs) and shows how these can support digital library users. It demonstrates processes related to integration of KOS like the Dewey Decimal Classification, $22^{nd}$ edition (DDC22) in DSpace software (http://www.dspace.org/) for organizing and retrieving (browsing and searching) scholarly objects. An attempt has been made to use the DDC22 available in Bengali language and highlights the required mechanisms for system-level integration. It may help a repository administrator to build an IDR (Institutional Digital Repository) integrated with SKOS-enabled multilingual subject access systems for supporting subject descriptors based indexing (DC.Subject metadata element), structured navigation (browsing) and efficient searching.

• Journal of the Korean Society for Library and Information Science
• /
• v.43 no.1
• /
• pp.313-332
• /
• 2009

Cross-language text categorization(CLTC) can classify documents automatically using training set from other language. In this study, collections appropriated for CLTC were extracted from KTSET. Classification performance of various CLTC methods were compared by SVM classifier using machine translation. Results showed that the classification performance in the order of poly-lingual training method, training-set translation and test-set translation. However, training-set translation could be regarded as the most useful method among CLTC, because it was efficient for machine translation and easily adapted to general environment. On the other hand, low performance was shown to be due to the feature reduction or features with no subject characteristics, which occurred in the process of machine translation of CLTC.

• Annual Conference on Human and Language Technology
• /
• 2021.10a
• /
• pp.414-418
• /
• 2021

다국어 음성인식은 단일언어 음성인식에 비해 높은 난이도를 보인다. 하나의 단일 모델로 다국어 음성인식을 수행하기 위해선 다양한 언어가 공유하는 음성적 특성을 모델이 학습할 수 있도록 하여 음성인식 성능을 향상시킬 수 있다. 본 연구는 딥러닝 음성인식 모델인 Wav2Vec2.0 구조를 변경하여 한국어와 영어 음성을 하나의 모델로 학습하는 방법을 제시한다. CTC(Connectionist Temporal Classification) 손실함수를 이용하는 Wav2Vec2.0 모델의 구조에서 각 언어마다 별도의 CTC 출력 계층을 두고 각 언어별 사전(Lexicon)을 적용하여 음성 입력을 다른 언어로 혼동되는 경우를 원천적으로 방지한다. 제시한 Wav2Vec2.0 구조를 사용하여 한국어와 영어를 잘못 분류하여 음성인식률이 낮아지는 문제를 해결하고 더불어 제시된 한국어 음성 데이터셋(KsponSpeech)에서 한국어와 영어를 동시에 학습한 모델이 한국어만을 이용한 모델보다 향상된 음성 인식률을 보임을 확인하였다. 마지막으로 Prefix 디코딩을 활용하여 언어모델을 이용한 음성인식 성능 개선을 수행하였다.