• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.317-325
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• 2017

In this paper, we try to classify Korean hedge sentences, which are regarded as not important since they express uncertainties or personal assumptions. Through previous researches to English language, we found dependency information of words has been one of important features in hedge classification, but not used in Korean researches. Additionally, we found that word embedding vectors include the word usage information. We assume that the word usage information could somehow represent the dependency information. Therefore, we utilized word embedding and neural networks in hedge sentence classification. We used more than one and half million sentences as word embedding dataset and also manually constructed 12,517-sentence hedge classification dataset obtained from online news. We used SVM and CRF as our baseline systems and the proposed system outperformed SVM by 7.2%p and also CRF by 1.2%p. This indicates that word usage information has positive impacts on Korean hedge classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.761-766
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• 2011

A hedge is a linguistic device to express uncertainties. Hedges are used in a sentence when the writer is uncertain or has doubt about the contents of the sentence. Due to this uncertainty, sentences with hedges are considered to be non-factual. There are many applications which need to determine whether a sentence is factual or not. Detecting hedges has the advantage in information retrieval, and information extraction, and QnA systems, which make use of non-hedge sentences as target to get more accurate results. In this paper, we constructed Korean hedge corpus, and extracted generalized hedge cue-word patterns from the corpus, and then used them in detecting hedges. In our experiments, we achieved 78.6% in F1-measure.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.133-146
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• 2015

This study is to investigate the causal relationship between exchange hedge and the net income of the shipbuilder through the unit root test and co-integration and vector autoregressive model(Vector Autoregressive Model: VAR). First, quarter net income of shipbuilders to order a unit root tests from 2000 to 2013 was used as a value after the Johnson transformation. In the same period, the return on bond futures(KTBF), three years bond yield(KTB3Y), America-Korea exchange differences are weekly data for each quarterly difference in value was converted by utilization, shipbuilding shares after log transformation which it was used. Also, structural change point investigation analysis to verify that looked to take advantage of the structural changes occur in the exchange hedge strategies affecting net income in the shipbuilding industry. Between the exchange hedge and net income of shipbuilders in structural change points detection and analysis showed that structural changes occur starting in 2004. In other words, strategy of shipbuilders about exchange hedge has occurred from "passive exchange hedge" to "active exchange hedge". The exchange hedge of the Korea shipbuilders through the estimation of the VAR was able to grasp that affect the profitability of mutual shipbuilders. Macroeconomic variables and stock prices could also check to see that affected the net income of the shipbuilding industry.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.19-24
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• 2017

The growing number of electronic financial transactions (e-banking) has entailed the rapid increase in security threats such as extortion and falsification of financial transaction data. Against such background, rigid security and countermeasures to hedge against such problems have risen as urgent tasks. Thus, this study aims to implement an improved case model by applying the Fraud Detection System (hereinafter, FDS) in a financial corporation 'A' using big data technique (e.g. the function to collect/store various types of typical/atypical financial transaction event data in real time regarding the external intrusion, outflow of internal data, and fraud financial transactions). As a result, There was reduction effect in terms of previous scenario detection target by minimizing false alarm via advanced scenario analysis. And further suggest the future direction of the enhanced FDS.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.3-12
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• 2021

Most researchers have experimentally evaluated the detection efficiency of reaction time-based concealed information tests (RT CIT). In experimental studies, two experimental paradigms have been mainly used to create a lying situation, mock-crime paradigm and personal-item paradigm. This study is aimed at testing the detection efficiency of RT CIT for the one that could be estimated as the same as the other, regardless of the experimental paradigms. In study 1, it was tested whether the effect size of RT CIT was different in the two experimental paradigms through meta-analysis. As a result of the meta-analysis of 39 studies, the effect size (Hedges'g = 1.330) of the mock-crime paradigm was slightly larger than that (Hedges'g = 1.145) of the personal-item paradigm, but no statistically significant difference was found. Study 2 was an experimental study using both the mock-crime and personal-item paradigms, it was conducted to determine whether the detection efficiency of RT CIT differs in the two experimental paradigms. As a result of ANOVA, it was found that the RT differences between the probe and irrelevant stimuli were not significant in the two experimental paradigms. In the experimental study, the effect size (Cohen's d) of the mock-crime and personal-item paradigms were 1.638 and 1.535, respectively. In the discussion section, the reason of the detection efficiency of RT CIT not affected by the experimental paradigms was discussed.