• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.359-367
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• 2022

Arabic skills are the tools by which children are prepared for the educational procedures on which their life depends. Deaf and hard of hearing students (DHH), must be able to grasp the same Arabic terms as hearing students and their different meanings in a context of different sentences less than what they are supposed to be due to their inability. However, problems arise in the same Arabic word and their different meanings in a context for (DHH) students since the way of comprehending such words does not meet the needs and circumstances of (DHH) students. Therefore, researchers introduce web-based method for Arabic words and their meanings in a context prototype that can overcome those problems. Methodology: The study sample consists of 30 (DHH) students at Al Amal City of Palestine, Gaza Region (GR). Those participants that agreed to take part in this study were recruited using a purposeful sampling method. Additionally, to examine the survey information descriptively, the Statistical Packages for social Sciences (SPSS) version 24.0 was used. A sign language teaching movie is utilized in the prototype to standardize the process and verify that Arabic vocabulary and their implications are comprehended. The Evolutionary Process Model of Prototype technique was utilized to create this system. Finding: The findings of this study show that the prototype built is workable and has the ability to help DHHS differentiate between phrases that have the same letters but distinct meanings. The findings of this study are expected to contribute to a better understanding and application of Development of Web-based Arabic Assessments for (DHH) Students in developing countries, which will help to increase the use of Development of Web-based Arabic for (HDD) students in those countries. The empirical models of Web-based Arabic for (DHH) students are established as a proof of concept for the proposed model. The results of this study are predicted to have a significant impact to the information system practitioners and to the body of knowledge.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.211-232
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• 2014

Recently, there is a growing interest toward social commerce using SNS(Social Networking Service), and the size of its market is also expanding due to popularization of smart phones, tablet PCs and other smart devices. Accordingly, various studies have been attempted but it is shown that most of the previous studies have been conducted from perspectives of the users. The purpose of this study is to derive user-centered CSF(Critical Success Factor) of social commerce from the previous studies and analyze the CSF perception gap between social commerce service providers and users. The CSF perception gap between two groups shows that there is a difference between ideal images the service providers hope for and the actual image the service users have on social commerce companies. This study provides effective improvement directions for social commerce companies by presenting current business problems and its solution plans. For this, This study selected Korea's representative social commerce business Ticket Monster, which is dominant in sales and staff size together with its excellent funding power through M&A by stock exchange with the US social commerce business Living Social with Amazon.com as a shareholder in August, 2011, as a target group of social commerce service provider. we have gathered questionnaires from both service providers and the users from October 22, 2012 until October 31, 2012 to conduct an empirical analysis. We surveyed 160 service providers of Ticket Monster We also surveyed 160 social commerce users who have experienced in using Ticket Monster service. Out of 320 surveys, 20 questionaries which were unfit or undependable were discarded. Consequently the remaining 300(service provider 150, user 150)were used for this empirical study. The statistics were analyzed using SPSS 12.0. Implications of the empirical analysis result of this study are as follows: First of all, There are order differences in the importance of social commerce CSF between two groups. While service providers regard Price Economic as the most important CSF influencing purchasing intention, the users regard 'Trust' as the most important CSF influencing purchasing intention. This means that the service providers have to utilize the unique strong point of social commerce which make the customers be trusted rathe than just focusing on selling product at a discounted price. It means that service Providers need to enhance effective communication skills by using SNS and play a vital role as a trusted adviser who provides curation services and explains the value of products through information filtering. Also, they need to pay attention to preventing consumer damages from deceptive and false advertising. service providers have to create the detailed reward system in case of a consumer damages caused by above problems. It can make strong ties with customers. Second, both service providers and users tend to consider that social commerce CSF influencing purchasing intention are Price Economic, Utility, Trust, and Word of Mouth Effect. Accordingly, it can be learned that users are expecting the benefit from the aspect of prices and economy when using social commerce, and service providers should be able to suggest the individualized discount benefit through diverse methods using social network service. Looking into it from the aspect of usefulness, service providers are required to get users to be cognizant of time-saving, efficiency, and convenience when they are using social commerce. Therefore, it is necessary to increase the usefulness of social commerce through the introduction of a new management strategy, such as intensification of search engine of the Website, facilitation in payment through shopping basket, and package distribution. Trust, as mentioned before, is the most important variable in consumers' mind, so it should definitely be managed for sustainable management. If the trust in social commerce should fall due to consumers' damage case due to false and puffery advertising forgeries, it could have a negative influence on the image of the social commerce industry in general. Instead of advertising with famous celebrities and using a bombastic amount of money on marketing expenses, the social commerce industry should be able to use the word of mouth effect between users by making use of the social network service, the major marketing method of initial social commerce. The word of mouth effect occurring from consumers' spontaneous self-marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers; in this context, the word of mouth effect should be managed as the CSF of social commerce. Third, Trade safety was not derived as one of the CSF. Recently, with e-commerce like social commerce and Internet shopping increasing in a variety of methods, the importance of trade safety on the Internet also increases, but in this study result, trade safety wasn't evaluated as CSF of social commerce by both groups. This study judges that it's because both service provider groups and user group are perceiving that there is a reliable PG(Payment Gateway) which acts for e-payment of Internet transaction. Accordingly, it is understood that both two groups feel that social commerce can have a corporate identity by website and differentiation in products and services in sales, but don't feel a big difference by business in case of e-payment system. In other words, trade safety should be perceived as natural, basic universal service. Fourth, it's necessary that service providers should intensify the communication with users by making use of social network service which is the major marketing method of social commerce and should be able to use the word of mouth effect between users. The word of mouth effect occurring from consumers' spontaneous self- marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers. in this context, it is judged that the word of mouth effect should be managed as CSF of social commerce. In this paper, the characteristics of social commerce are limited as five independent variables, however, if an additional study is proceeded with more various independent variables, more in-depth study results will be derived. In addition, this research targets social commerce service providers and the users, however, in the consideration of the fact that social commerce is a two-sided market, drawing CSF through an analysis of perception gap between social commerce service providers and its advertisement clients would be worth to be dealt with in a follow-up study.

• English Language & Literature Teaching
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• v.13 no.3
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• pp.1-22
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• 2007

The study examined the effects of explicit derivational morphology instruction (henceforth DMI) on the incidental vocabulary acquisition and reading comprehension of 132 Korean 1st-year high school students who responded to a battery of tests (two vocabulary tests and a reading comprehension test). Multiple statistical tools were used to analyze the data: Analysis of Covariance (ANCOVA), Analysis of Variance (ANOVA), Simple Regression Analysis, Tests of Simple Main Effects, and effect size computation using Cohen's d. The results indicated that (a) DMI enhanced students' ability to infer word meanings in context, (b) DMI promoted high proficiency students' reading comprehension, whereas it impeded intermediate proficiency students' reading comprehension, (c) vocabulary knowledge has a strong positive predictive value for reading comprehension, and (d) the gaps of vocabulary knowledge across proficiency levels were still substantial, despite the observation that DMI promoted students' vocabulary acquisition. These results have a bearing on English as Foreign Language (EFL) reading pedagogy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.17-20
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• 2016

딥러닝 기법이 발달함에 따라 텍스트에 내재된 의미 및 구문을 어떠한 벡터 공간 상에 표현하기 위한 언어 모델이 활발히 연구되어 왔다. 이를 통해 자연어 처리를 기반으로 하는 감성 분석 및 문서 분류, 기계 번역 등의 분야가 진보되었다. 그러나 대부분의 언어 모델들은 텍스트에 나타나는 단어들의 일반적인 패턴을 학습하는 것을 기반으로 하기 때문에, 문서 요약이나 스토리텔링, 의역된 문장 판별 등과 같이 보다 고도화된 자연어의 이해를 필요로 하는 연구들의 경우 주어진 텍스트의 주제 및 의미를 고려하기에 한계점이 있다. 이와 같은 한계점을 고려하기 위하여, 본 연구에서는 기존의 LSTM 모델을 변형하여 문서 주제와 해당 주제에서 단어가 가지는 문맥적인 의미를 단어 벡터 표현에 반영할 수 있는 새로운 언어 학습 모델을 제안하고, 본 제안 모델이 문서의 주제를 고려하여 문장을 자동으로 생성할 수 있음을 보이고자 한다.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.141-149
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• 2009

An emphasis on teaching suprasegmental features of English, specifically English rhythm, is essential in order to improve the 'intelligibility' of the pronunciation of Korean EFL learners among interlocutors who use English as a Lingua Franca(ELF). By redefining the ELF suggested by Jenkins (2000, 2002), this paper argues that Lingua Franca Core (LFC) must include suprasegmental features such as 'stress-based rhythm' and word stress. However, because 'isochrony' is difficult to measure in a foot, the rhythm unit must be expanded to an intonational phrase which has prominence in it and the rhythm of the unit can be measured by calculating the duration of each segment in context The rhythmic pattern of Korean learners of English and that of native speakers or other non-native English speakers can then be calculated and compared by using correlation coefficients of the segmental duration. In terms of sociolinguistic factors, improving the 'comprehensibility' and 'accentedness' of Korean EFL learners' pronunciation is also important in international communication, which calls for more emphasis on suprasegmental features.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.39-46
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• 2009

This study compares the perception of English high tense and lax vowels (/i, I, u, $\mho$/) by English speakers and Korean speakers of English. The four vowels were produced in /hVd/ context by a native speaker of English, and each word's vowel duration was manipulated to range from 170ms to 290ms in 30ms increments. Two English speakers and six Korean speakers of English were asked to listen to pairs of tense and lax vowel words with manipulated vowel durations and to identify the pair by choosing either heed-hid or hid-heed for front vowels and either who'd-hood or hood-who'd for back vowels. The results show that English speakers distinguished tense vowels from lax vowels with 100% accuracy regardless of the different durations, compared to 62% accuracy for Korean speakers of English. Most errors occurred for lengthened lax vowels and shortened tense vowels. The results of this study demonstrate that Korean speakers mainly rely on vowel duration as a cue to discriminate the tense and lax vowels. The theoretical and pedagogical implications of this finding are discussed.

• Research in Mathematical Education
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• v.11 no.2
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• pp.127-141
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• 2007

This paper compares and analyzes mathematics teachers' understanding of students' mathematical comprehension after experiences with the Cognitively Guided Instruction (CGI) or the Development of Mathematical Ideas (DMI) teaching strategies. This report sheds light on current issues confronted by the educational system in the context of mathematics teaching and learning. In particular, the declining rate of mathematical literacy among adolescents is discussed. Moreover, examples of CGI and DMI teaching strategies are presented to focus on the impact of these teaching styles on student-centered instruction, teachers' belief, and students' mathematical achievement, conceptual understanding and word problem solving skills. Hence, with a gradual enhancement of reformed ways of teaching mathematics in schools and the reported increase in student achievement as a result of professional development with new teaching strategies, teacher professional development programs that emphasize teachers' understanding of students' mathematical comprehension is needed rather than the currently dominant traditional pedagogy of direct instruction with a focus on teaching problem solving strategies.

• Knowledge Management Research
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• v.12 no.5
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• pp.1-10
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• 2011

Forming a network, through Social Network Services (SNS), among a group of people who share the same hobby or interests could increase the information sharing among the members at an exponential rate. Moreover, SNS users' behavior extends beyond the traditional introverted consumption behavior to a proactive behavior by owning or actively sharing product information. For firms, such proactive consumer behavior translates into marketing effects such as the word of mouth (WOM) effect. Therefore, SNSs are accepted not only as a communications channel between firms and consumers but also as marketing channel, suggesting the possibility of a new revenue source. In this context, we will explore into the factors of SNS contents which conserve firms' image and product information, and effects of the factors on consumer attitude and WOM.

• Annual Conference on Human and Language Technology
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• 1998.10c
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• pp.425-429
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• 1998

본 논문은 문맥에서 추출한 가중치 정보를 이용한 한국어 동사의 의미 중의성 해소 모델을 제안한다. 중의성이 있는 단어가 쓰인 문장에서 그 단어의 의미 결정에 영향을 주는 단어들로 의미 결정자 벡터를 구성하고, 사전에서 그 단어의 의미 항목에 쓰인 단어들로 의미 항목 벡터를 구성한다. 목적 단어의 의미는 두 벡터간의 유사도 계산에 의해 결정된다. 벡터간의 유사도 계산은 사전에서 추출된 공기 관계와 목적 단어가 속한 문장에서 추출한 거리와 품사정보에 기반한 가중치 정보를 이용하여 이루어진다. 4개의 한국어 동사에 대해 내부실험과 외부실험을 하였다. 내부 실험은 84%의 정확률과 baseline을 기준으로 50%의 성능향상, 외부 실험은 75%의 정확률과 baseline을 기준으로 40 %의 성능향상을 보인다.