• 정보관리학회지
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• 제2권1호
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• pp.108-135
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• 1985

이용자와 시스템간에 상호작용이 이루어질수 있는 온라인 정보검색 시스템에서는 검색결과에 대한 이용자의 피이드백을 이용하여 검색질문을 수정함으로써 시스템의 성능을 향상시킬수 있다. 본 논문에서는 샐톤과 우가 제시한 검색질문의 자동수정 모형을 통제된 키이워어드 시스템에 적용시켜 보았다.

• 정보관리학회지
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• 제16권2호
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• pp.49-80
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• 1999

본 연구는 자연어 비불리언 탐색에서 탐색결과에 근거하여 질의를 수정, 확장, 결합하여 검색효과를 향상시키는 시스템들을 개념모델별로 성능을 고찰하고, 성능에 영향을 끼치는 요소들을 분석하여, 이론적인 개념의 틀을 제시하였다. 용어의 가중치기법, 문헌의 순위화방법, 용어선정알고리즘, 질의확장에 사용된 문헌수와 용어수, 적합성판정정보의 출처 및 척도, 배움표본의 크기, 부적합문헌정보의 사용여부, 용어확장방법, 질의의 크기, DB의 종류와 크기 등에 의해 영향을 받는 것으로 분석되었다.

• 아태비즈니스연구
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• 제11권3호
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• pp.123-136
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• 2020

Purpose - This study is to verify the impact of the documentation of key audit matters on the value relevance of accounting information in accordance with the revised accounting audit standards in 2017. Investors will be able to identify the company's significant financial risks through key audit matters and use them to make investment decisions. Design/methodology/approach - From 2011 to 2019, the final sample is 290, based on the December settlement of accounts listed on the securities market. Ohlson (1995) was used to verify the incremental link between net income and the book value as a determinant of corporate value. Findings - First, the key audit matters in the financial industry was found to have a negative (-) effect that was significant to the value relevance of accounting Information. In addition, the value of the interaction between the key audit matters and the net income is a significant (+) relationship with the share price and the value of the interaction between the key audit matters and the book value is a significant (-) relationship with the share price. This means that the key audit matters is the determining factor of corporate value, positively reflects the accounting information in net income and negatively reflects the accounting information in book value. Second, among the key audit matters, the fair value assessment of financial instruments and the adequacy of premiums reserve have a significant impact on the value relevance of accounting information. Research implications or Originality - The results of this study suggest that investors recognize key audit matters as information about the company's major financial risks and reflect them differently in the value relevance of accounting information.

• Smart Structures and Systems
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• 제30권3호
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• pp.303-315
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• 2022

The degradation of wheel tread may result in serious hazards in the railway operation system. Therefore, timely wheel defect diagnosis of in-service trains to avoid tragic events is of particular importance. The focus of this study is to develop a novel wheel defect detection approach based on the relevance vector machine (RVM) which enables online detection of potentially defective wheels with trackside monitoring data acquired under different running-speed conditions. With the dynamic strain responses collected by a trackside monitoring system, the cumulative Fourier amplitudes (CFA) characterizing the effect of individual wheels are extracted to formulate multiple probabilistic regression models (MPRMs) in terms of multi-kernel RVM, which accommodate both variables of vibration frequency and running speed. Compared with the general single-kernel RVM-based model, the proposed multi-kernel MPRM approach bears better local and global representation ability and generalization performance, which are prerequisite for reliable wheel defect detection by means of data acquired under different running-speed conditions. After formulating the MPRMs, we adopt a Bayesian null hypothesis indicator for wheel defect identification and quantification, and the proposed method is demonstrated by utilizing real-world monitoring data acquired by an FBG-based trackside monitoring system deployed on a high-speed trial railway. The results testify the validity of the proposed method for wheel defect detection under different running-speed conditions.

• 한국컴퓨터정보학회논문지
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• 제4권1호
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• pp.21-27
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• 1999

본 논문은 단어들의 유사도를 이용하여 문서들을 자동으로 분류하는 새로운 방법을 제안한다. 단어들 중에서 의미있는 단어들을 찾아내기 위하여 자동색인 방법을 이용하였으며. 두 번째로 본 논문에서 제안한 확률 모델을 이용하여 각 단어들의 문서와의 연관관계를 분석하였다. 이를 토대로 분류를 가능하게 하기 위한 프로파일을 생성한다. 본 논문에서는 유전자 알고리즘과 신경망에 관련된 10개의 문서에 대하여 실험하여 유전자 알고리즘과 신경망에 해당하는 프로파일을 생성하였다.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.863-875
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• 2017

The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.303-313
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• 2020

This study investigates the factors affecting Industry 4.0 adoption in the curriculum of university students in Ho Chi Minh City, Vietnam. Universities need to respond to the changing faces of Industry 4.0 and, hence, Education 4.0. A mixed method including both qualitative and quantitative methodologies was utilized. An in-depth interview was carried out for exploring, reviewing, and testing content validity of constructs and measurement items. The pilot study was conducted with 120 respondents. The conceptual model and hypotheses were developed using data collected by a questionnaire survey distributed to 584 respondents by both electronic and paper forms with non-probability and convenience sampling techniques. The result of structural equation modeling showed that occupation relevance, skills, facility conditions, and social influence impacted on the intermediates variables, namely, relevance advantage, perceived usefulness, behavioral intention-to-use, and actual use. The independent variables are occupation relevance, skills, facility conditions, and social influence. They impact actual use through mediating constructs such as relevance advantage, perceived usefulness, and behavioral intention-to-use. The findings suggest that universities and students' efforts aimed at increasing the factors' perceptions of adoption of Industry 4.0 will contribute to implementation success, where success is defined as effectual usage of Industry 4.0.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.664-671
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• 2023

최근 다양한 거대 언어모델(Large Language Model)들이 개발되면서 프롬프트 엔지니어링의 대한 다양한 연구가 진행되고 있다. 본 논문에서는 퓨삿 학습 환경에서 개체명 인식의 성능을 높이기 위해서 제안된 템플릿이 필요 없는 프롬프트 튜닝(Template-free Prompt Tuning) 방법을 이용하고, 이 방법에서 사용된 라벨 단어 집합 생성 방법에 Maximal Marginal Relevance 알고리즘을 적용하여 해당 개체명에 대해 보다 다양하고 구체적인 라벨 단어 집합을 생성하도록 개선하였다. 실험 결과, 'LOC' 타입을 제외한 나머지 개체명 타입에서 'PER' 타입은 0.60%p, 'ORG' 타입은 4.98%p, 'MISC' 타입은 1.38%p 성능이 향상되었고, 전체 개체명 인식 성능은 1.26%p 향상되었다. 이를 통해 본 논문에서 제안한 라벨 단어 집합 생성 기법이 개체명 인식 성능 향상에 도움이 됨을 보였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.133-141
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• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• 유통과학연구
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• 제16권2호
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• pp.83-88
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• 2018

Purpose - For distribution corporate, the method of recognizing sales revenue may be different depending on the type of distribution transaction. Until the change in accounting standards for revenue recognition was made in 2002, the distribution corporate recognized the full amount of sales of goods regardless of the type of transaction. However, in accordance with accounting standards for revenue recognition, which began to be applied in 2003, distribution corporate differ in sales revenue recognition by transaction type. The Purpose of this study is to analyze the impact of sales revenue on the corporate value after the change of the revenue recognition accounting standards. Research design, data, and methodology - We selected a comprehensive wholesale and retail corporate listed on Korea Exchange. The research model extends the Ohlson(1995) model and regresses whether sales revenue affecting the corporate value is discriminatory value relevance between the corporate affected by changes in accounting standards for revenue recognition and those not. Results - The results of the analysis are as follows. First, The average value of stock price, net asset per share, and earnings per share are all higher than those before the change of accounting standards for revenue recognition. However, the average value of sales per share is lower than that before the change of accounting standards for revenue recognition. Second, the relationship between corporate value and net asset per share, earnings per share and sales per share, the coefficient of net asset per share, earnings per share and sales per share are all statistically significant positive value. Therefore, in explaining corporate value, besides net asset per share and earnings per share, sales per share provides additional information. And the coefficient of interaction variable between accounting standard change and sales per share is a statistically significant positive value. This result indicating that after the change of the revenue recognition accounting standards the usefulness of sales revenue has increased. Conclusions - The change in accounting standards for revenue recognition led to a decrease in distribution corporate sales revenue but the higher the relevance of the corporate value of the sales revenue information. These results shows that the change of accounting standards that reflects the transaction type of retailers was a revision to increase the value relevance of sales revenue in valuation of corporate value.