• Title/Summary/Keyword: language usage

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Robustness of Differentiable Neural Computer Using Limited Retention Vector-based Memory Deallocation in Language Model

  • Lee, Donghyun;Park, Hosung;Seo, Soonshin;Son, Hyunsoo;Kim, Gyujin;Kim, Ji-Hwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.837-852
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    • 2021
  • Recurrent neural network (RNN) architectures have been used for language modeling (LM) tasks that require learning long-range word or character sequences. However, the RNN architecture is still suffered from unstable gradients on long-range sequences. To address the issue of long-range sequences, an attention mechanism has been used, showing state-of-the-art (SOTA) performance in all LM tasks. A differentiable neural computer (DNC) is a deep learning architecture using an attention mechanism. The DNC architecture is a neural network augmented with a content-addressable external memory. However, in the write operation, some information unrelated to the input word remains in memory. Moreover, DNCs have been found to perform poorly with low numbers of weight parameters. Therefore, we propose a robust memory deallocation method using a limited retention vector. The limited retention vector determines whether the network increases or decreases its usage of information in external memory according to a threshold. We experimentally evaluate the robustness of a DNC implementing the proposed approach according to the size of the controller and external memory on the enwik8 LM task. When we decreased the number of weight parameters by 32.47%, the proposed DNC showed a low bits-per-character (BPC) degradation of 4.30%, demonstrating the effectiveness of our approach in language modeling tasks.

Integration of computer-based technology in smart environment in an EFL structures

  • Cao, Yan;AlKubaisy, Zenah M.
    • Smart Structures and Systems
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    • v.29 no.2
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    • pp.375-387
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    • 2022
  • One of the latest teaching strategies is smart classroom teaching. Teaching is carried out with the assistance of smart teaching technologies to improve teacher-student contact, increase students' learning autonomy, and give fresh ideas for the fulfillment of students' deep learning. Computer-based technology has improved students' language learning and significantly motivating them to continue learning while also stimulating their creativity and enthusiasm. However, the difficulties and barriers that many EFL instructors are faced on seeking to integrate information and communication technology (ICT) into their instruction have raised discussions and concerns regarding ICT's real worth in the language classroom. This is a case study that includes observations in the classroom, field notes, interviews, and written materials. In EFL classrooms, both computer-based and non-computer-based activities were recorded and analyzed. The main instrument in this study was a survey questionnaire comprising 43 items, which was used to examine the efficiency of ICT integration in teaching and learning in public schools in Kuala Lumpur. A total of 101 questionnaires were delivered, while each responder being requested to read the statements provided. The total number of respondents for this study was 101 teachers from Kuala Lumpur's public secondary schools. The questionnaire was randomly distributed to respondents with a teaching background. This study indicated the accuracy of utilizing Teaching-Learning-Based Optimization (TLBO) in analyzing the survey results and potential for students to learn English as a foreign language using computers. Also, the usage of foreign language may be improved if real computer-based activities are introduced into the lesson.

Syllable-Level Lightweight Korean POS Tagger using Transformer Encoder (트랜스포머 인코더를 활용한 음절 단위 경량화 형태소 분석기)

  • Suyoung Min;Youngjoong Ko
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.10
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    • pp.553-558
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    • 2024
  • Morphological analysis involves segmenting morphemes, the smallest units of meaning or grammatical function in a language, and assigning part-of-speech tags to each morpheme. It plays a critical role in various natural language processing tasks, such as named entity recognition and dependency parsing. Much of modern natural language processing relies on deep learning-based language models, and Korean morphological analysis can be broadly categorized into sequence-to-sequence methods and sequential labeling methods. This study proposes a morphological analysis approach using the transformer encoder for sequential labeling to perform syllable-level part-of-speech tagging, followed by morpheme restoration and tagging through a pre-analyzed dictionary. Additionally, the CBOW method was used to extract syllable-level embeddings in lower dimensions, designing a lightweight morphological analyzer model with reduced parameters. The proposed model achieves fast inference speed and low parameter usage, making it efficient for use in resource-constrained environments.

Member/Group License Mechanism for Secure and Flexible Sharing of Protected Contents in DRM Systems (DRM 기술로 보호된 컨텐츠의 융통성 있는 공유를 위한 멤버/그룹 라이선스 메커니즘)

  • Chang Hai Jin
    • The KIPS Transactions:PartC
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    • v.11C no.6 s.95
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    • pp.739-746
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    • 2004
  • License mechanisms are the key elements in almost all DRM(digital rights management) systems. The license mechanisms are designed for the clear identification and enforcement of contents, principals, and usage rules in DRM systems. But current license mechanisms are lacking in the flexibility for the secure and efficient sharing of the contents among the members of a group such as a family or a part of an enterprise. This paper suggests a new license mechanism for efficient and secure sharing of contents in DRM systems among the members of a group. We named it member/group license mechanism. The mechanism extends the current license mechanisms by introducing new concepts such as group licenses, member licenses, and derivation relationships between licenses.

Analysis of Search Engine Use, Search Behaviors and Aptitude by Web Users (웹 이용자의 검색엔진 활용 및 탐색 행위와 성향 분석)

  • Rieh, Hae-Young
    • Journal of the Korean Society for Library and Information Science
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    • v.36 no.3
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    • pp.69-91
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    • 2002
  • This study examines overall user experience associated with Web search engine use including selection, usage of search features, evaluation. The data were collected through individual interviews with 28 faculty members and graduate students. It was found that users tend to select a search engine based on experience and knowledge of certain features and familiarity with an engine itself more than based on previous experience with search results. The results showed the users had mixed opinions regarding cross language retrieval while they did not believe the usage of operators effect the search results. It appears that users are interested in interface design as well as the accuracy of search results.

A Construction of the Network Type Database Management System for Model Ice (빙해수조 모형빙에 관한 네트워크형 데이터베이스 구축)

  • Lee, Jae-Hwan;Kim, In-Soo;Choi, Bong-Kyun;Lee, Chun-Ju
    • Journal of the Society of Naval Architects of Korea
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    • v.51 no.1
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    • pp.51-57
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    • 2014
  • In the KIOST MOERI model ice basin, a lot of experiments to find the material properties of model ice and model ship tests are being performed. And therefore many data information was produced, yet it was saved as excel data format. In order to manage and use the data more effectively and systematically, a proper database management is required. To make realistic engineering DBMS(database management system), understanding of test process, the usage of data, design of data schema and computer language and system management are required. In this paper, basic design process and usage of DBMS based on network and multiple user concept is introduced.

An Analysis of Key Elements for FinTech Companies Based on Text Mining: From the User's Review (텍스트 마이닝 기반의 자산관리 핀테크 기업 핵심 요소 분석: 사용자 리뷰를 바탕으로)

  • Son, Aelin;Shin, Wangsoo;Lee, Zoonky
    • The Journal of Information Systems
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    • v.29 no.4
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    • pp.137-151
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    • 2020
  • Purpose Domestic asset management fintech companies are expected to grow by leaps and bounds along with the implementation of the "Data bills." Contrary to the market fever, however, academic research is insufficient. Therefore, we want to analyze user reviews of asset management fintech companies that are expected to grow significantly in the future to derive strengths and complementary points of services that have been provided, and analyze key elements of asset management fintech companies. Design/methodology/approach To analyze large amounts of review text data, this study applied text mining techniques. Bank Salad and Toss, domestic asset management application services, were selected for the study. To get the data, app reviews were crawled in the online app store and preprocessed using natural language processing techniques. Topic Modeling and Aspect-Sentiment Analysis were used as analysis methods. Findings According to the analysis results, this study was able to derive the elements that asset management fintech companies should have. As a result of Topic Modeling, 7 topics were derived from Bank Salad and Toss respectively. As a result, topics related to function and usage and topics on stability and marketing were extracted. Sentiment Analysis showed that users responded positively to function-related topics, but negatively to usage-related topics and stability topics. Through this, we were able to extract the key elements needed for asset management fintech companies.

Enhancement of Semantic Interoper ability in Healthcare Systems Using IFCIoT Architecture

  • Sony P;Siva Shanmugam G;Sureshkumar Nagarajan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.881-902
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    • 2024
  • Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

Evaluating English Loanwords and Their Usage for Professional Translation, Focusing on News Texts

  • Bokyung Noh
    • International Journal of Advanced Culture Technology
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    • v.12 no.2
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    • pp.161-166
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    • 2024
  • As globalization has accelerated, the use of English loanwords is increasing in South Korea. In this paper, we have analyzed news stories from four Korean quality newspapers-Chosun Ilbo, Dong-A Ilbo, KyungHyang Sinmun, and Chung-Ang Ilbo to investigate the usage of English loanwords in news texts. Thirty-eight news stories on life, politics, business and IT were collected from the four newspapers and then analyzed based on the five types of loanwords-Direct, Mixed Code Combination, Clipping and Neologism and Double Notation, partly following Lee's and Rudiger's classification. As a result, the followings were revealed: first, the use of the category Direct was overwhelming the others with 90%, indicating that English loanwords were not translated from its source language and introduced into Korean directly with little modification; second, the use of English loanwords was significantly higher in the sections of business and IT than in other sectors, implying that English loanwords function in a similar way as a lingua franca does within those fields. Furthermore, the linguistic trends can provide a basic guide for translators to make an informed decision between the use of English loanwords and its translated Korean version in English-into Korean translation.

A Study on the Korean University Students' Usage of Foreign Language Queries in Scholarly Information Retrieval (학술정보검색을 위한 국내 대학생의 외국어 탐색문 활용에 관한 연구)

  • Lee, Bo Eun;Lee, Jee Yeon
    • Journal of the Korean Society for information Management
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    • v.36 no.1
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    • pp.95-116
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    • 2019
  • This study focused on understanding the Korean university students' (both undergraduates and graduates) use of foreign language for scholarly information retrieval especially in different search strategies employed based on users' characteristics. A new model was developed based on Ellis's behavioral model of information seeking strategies. The research applied both quantitative and qualitative methods to analyze the data. The students used a variety of foreign language information seeking strategies at different stages of academic information retrieval based on his/her field of study or level of education. The liberal arts and social science students had more difficulty in selecting proper search terms in the foreign language than the science and technology students. This difficulty resulted in less preference for using foreign language queries by the liberal arts and social science students. The students relied more on the bibliographic and citation information in scholarly information retrieval using foreign language queries than the Korean queries. The research outcomes should provide some guidelines on how the Korean university libraries offer information literacy programs and other services based on the patrons' characteristics.