• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.881-888
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• 2013

A pre-analyzed dictionary is used to increase the speed and the accuracy of morphological analyzers and to decrease the over-generation. However, if the dictionary includes 'Insufficiently-analyzed word-phrases', which do not include all the possible analysis of the word-phrase, it may cause the decrease of the analysis accuracy. In this paper, we measure the accuracy changes according to the number of word-phrase frequency and the size changes of corpus by Sejong corpus. And performance of integrate system(SMA with pre-dictionary) is highest when sufficient analysis rate of pre-dictionary is more than 99.82%. Also pre-dictionary is constructed with word-phrase that frequency more than 32(64) when size of corpus is 1,600,000(6,300,000) word-phrase.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.117-128
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• 2017

Purpose: This study analyzes automobile quality review data to develop alternative analytical method of informal data. Existing methods to analyze informal data are based mainly on the frequency of informal data, however, this research tries to use correlation information of each informal data. Method: After sentimental analysis to acquire the user information for automobile products, three classification methods, that is, $na{\ddot{i}}ve$ Bayes, random forest, and support vector machine, were employed to accurately classify the informal user opinions with respect to automobile qualities. Additionally, Word2vec was applied to discover correlated information about informal data. Result: As applicative results of three classification methods, random forest method shows most effective results compared to the other classification methods. Word2vec method manages to discover closest relevant data with automobile components. Conclusion: The proposed method shows its effectiveness in terms of accuracy and sensitivity on the analysis of informal quality data, however, only two sentiments (positive or negative) can be categorized due to human errors. Further studies are required to derive more sentiments to accurately classify informal quality data. Word2vec method also shows comparative results to discover the relevance of components precisely.

• Proceedings of the Korean Magnestics Society Conference
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• 2003.06a
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• pp.174-175
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• 2003

• Journal of the East Asian Society of Dietary Life
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• v.20 no.4
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• pp.606-618
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• 2010

The study investigated how 'word of mouth' originates in the chain restaurant industry. It has long been acknowledged that 'word of mouth' is a critical factor for the success of a restaurant business due to its targetability and cost effectiveness. A review of the literature revealed four antecedents of 'word of mouth': service quality, perceived value, satisfaction, and relationship quality. Based on the theoretical/empirical relationships between those constructs, a structural model composed of the hypotheses was proposed. The structural model was tested with data collected from 471 chain restaurant patrons. The structural equation modeling analysis revealed that five constructs in the proposed model are interrelated, and during this process, word of mouth is formed in the chain restaurant industry. A positive relationship between service quality and satisfaction (0.265, p<0.05), service quality and perceived value (0.831, p<0.05), service quality and relationship quality (0.465, p< 0.05), and service quality and WOM (0.263, p< 0.05) were found, indicating that service quality is a key prerequisite for word of mouth and other constructs proposed in the model. It was revealed that perceived value doe not have a direct impact on WOM formation (t=1.275, p=0.202), but a positive relationship between perceived value and satisfaction (0.293, p<0.05) and between satisfaction and WOM (0.627, p< 0.05) were found. Therefore, it was concluded that patrons' perceived value influences word of mouth formation, but that impact is mediated by satisfaction. During this process, relationship quality also plays a mediating role in generating word of mouth. Based on data analysis, theoretical/managerial implications are discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.327-338
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• 2014

The purpose of this study is to investigate what the characteristics of word-of-mouth on SNS and how these factors credibility for information's source and acceptance of word-of-mouth. We proposed study model was set through overall theoretical investigation. The 179 Valid survey data were gathered from the user who have prior experience in SNS. According to factor analysis, characteristic of word-of-mouth information on SNS were classified into consensus and neutrality. And credibility for information's source and acceptance of word-of-mouth were composed sing dimension. The Hypothesis inspection says that all variables were positively correlated with each other. And consensus and valance have positive influence on credibility for information's source. Also credibility for information's source influence on acceptance of word-of-mouth and valance have positive affect trust for information's source. Several academic and practical implications are yield accordingly. Especially this study intention to provide basis which can be used for all business's effective marketing activity.

• Education of Primary School Mathematics
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• v.10 no.2
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• pp.141-149
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• 2007

It is undeniably important to bring up a solution capability of arithmetic word problems in the elementary mathematical education. The goal of this study is to acquire the implication for remedial instruction on arithmetic word problems solving through surveying elementary school students' difficulties in the solving of arithmetic word problems. In order to do it, this study was intended to analyze the following two aspects. First, it was analyzed that they generally felt more difficulties in which field among addition, subtraction, multiplication and division word problems. Second, with the result of the first analysis, it was examined that they solved it by imagining as which sphere of the other word problems. Also, the cause of their error on the word problem solving was analyzed by the interview. From the foregoing analyses, the following implications for remedial instruction on arithmetic word problems solving are acquired. First, the accumulation of learning deficiency must be diminished through the remedial instruction. Second, it must help students to understand the given problem and to make of what the goal of problem is. Third, it must help students to form a good habit for reading the problem and to understand the context of problem. forth, the teacher must help students to review and reflect their problem-solving processes.

• Asia Marketing Journal
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• v.18 no.3
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• pp.1-18
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• 2016

The purpose of this paper is to examine empirically how to balance advertising expenditure before and after launch with regard to the direction of word of mouth in the motion picture industry. The vector auto-regression model is applied to assess the dynamic impact of advertising and word of mouth on sales. Empirical data, including advertising, word of mouth, and sales (the number of entries) of 83 movies are used for analysis. The research results show that for a movie having more positive word of mouth in the pre- and post-launch periods, it is worthwhile to spend the advertising budget in the pre-launch period only and to spare it in post-launch period. However, it is worthwhile to spare the advertising budget in the pre-launch period for movies having less positive word of mouth before and after launch, and to concentrate spending in post-launch period instead. Mangers who handle products and services facing shortened lifecycles, such as games, eBooks, and digital music contents, need to check the quality of pre-launch word of mouth for their advertising budget decisions in the pre- and post-launch periods and spend more of the advertising budget in the post- (pre-) launch period if pre-launch word of mouth is negative (positive). For products and services with a shortened lifecycle, it is recommended to spend more of the advertising budget in the post- (pre-) launch period if pre-launch word of mouth is negative (positive).

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.295-312
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• 2011

This study conducted time-series analysis on domestic studies related to entrepreneurship for more than last 50 years by integrating the co-word analysis method of intellectual structure analysis into the study of entrepreneurship. The co-word analysis method is a quantitative analysis method to analyze the overall trend of the study and further study topics by visualizing the information between study topics and arranging the topics on two-dimensional plane and the study result showed largely four phases and the direction of the study path. According to the analysis, the study is started at embryonic study phase(third quadrant), the study topic of independent study phase(second quadrant) is a phase to be a settled independent area as a study and the topics of the study include topics of the study reflecting the situation of the times. At growing study phase(first quadrant) study topics which are closely related to the study topic are arranged, and the topics, the center of the study, are positioned at the study topics of maturity phase(4th quadrant).

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.121-124
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• 1993

This paper is a study on the word recognition using neural network. A limited vocabulary, speaker independent, isolated word recognition system has been built. This system recognizes isolated word without performing segmentation, phoneme identification, or dynamic time wrapping. It needs a static pattern approach to recognize a spatio-temporal pattern. The preprocessing only includes preceding and tailing silence removal, and word length determination. A LPC analysis is performed on each of 24 equally spaced frames. The PARCOR coefficients plus 3 other features from each frame is extracted. In order to simplify a structure of neural network, we composed binary code form to decrease output nodes.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.3
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• pp.293-304
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• 2014

This study investigated the effect of consumers' shopping value in social commerce on consumers' fashion shopping satisfaction and future behavioral intention. Respondents were limited to consumers aged 20 to 39 who had recently purchased fashion products through social commerce over the last month. The final analysis used 318 samples. Descriptive statistics, Cronbach's alpha, confirmatory factor analysis, and structural equation model were conducted. The results are as follows. First, hedonic and utilitarian shopping value significantly influenced consumers' fashion shopping satisfaction in social commerce. Hedonic shopping value was more strongly related to fashion shopping satisfaction. Second, fashion shopping satisfaction in social commerce had an effect on behavioral intention and SNS word-of-mouth. Behavioral intention consisted of repurchase intention and recommend intention. SNS word-of-mouth intention represented word-of-mouth intention using SNS such as Facebook and Twitter. When consumers were satisfied with their shopping experience, they were willing to have re-patronage intentions and SNS word-of-mouth intention. The results suggested that social commerce should try to raise consumers' fashion shopping satisfaction in social commerce and offer a pleasant experience. Also, social commerce should try to be connected to SNS such as Facebook and Twitter to increase word-of-mouth intention.