• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.5
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• pp.690-704
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• 2014

This study examined the risk perception in internet shopping by Chinese and analyzed the effects of risk perception on internet word-of-mouth acceptance and transmission. This analysis was conducted with data collected from 373 Chinese individuals in their 20s. Data were analyzed with factorial analysis, cluster analysis, ANOVA, multiple regression analysis, Chi-square test, and Cronbach's ${\alpha}$ using SPSS 18.0. The results were: 1) The factor analysis of risk perception extracted four factors: fashion/social psychological risk, product risk, transaction risk, and economic risk. The cluster analysis classified them into: Group with low-risk, Group with high-risk, Group with economic risk, and Group with medium-risk. 2) Group with high-risk and Group with economic risk had a higher word-of-mouth acceptance than other groups. The Group with a high-risk had more word-of-mouth transmission than other groups. 3) It was found that when word-of-mouth was accepted, the factual information about fashion products (size and material) was most referred to, and that the overall evaluation of satisfaction and dissatisfaction was most conveyed when word-of-mouth was conveyed. 4) Internet word-of-mouth acceptance was affected by product risk, economic risk, and transaction risk. Internet word-of-mouth transmission was affected by economic risk, and fashion/social psychological risk, product risk, and transaction risk.

• English Language & Literature Teaching
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• v.10 no.2
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• pp.67-87
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• 2004

The purpose of this paper is to show how the coda of a syllable and word-final clusters are represented in the English syllable structure. Previous theories on the syllable assume that there is only one segment in the coda position. And, as we know, the theories that license only one segment in the coda make it difficult to syllabicate the word-final cluster appropriately when more than two segments in the word-final cluster are encountered. I considered three approaches: the previous syllable structure (Selkirk, 1982; Borowsky 1989), sonority sequencing (Giegerich, 1992; Roca, 1999) and feature analysis (Goldsmith, 1990), But, all the considered methods don't give us a satisfactory explanation regarding word-final clusters. Finally, I will suggest a modified syllable representation as an alternative by placing two different appendixes under the Phonological Word which forms a constituent above the syllable node. From this it is possible to explain the former problematic word-final clusters including morphological information asan inflectional suffix in the structure.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.191-197
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• 2019

Morphological analysis is used for searching sentences and understanding context. As most morpheme analysis methods are based on predefined dictionaries, the problem of a target word not being registered in the given morpheme dictionary, the so-called unregistered word problem, can be a major cause of reduced performance. The current practical solution of such unregistered word problem is to add them by hand-write into the given dictionary. This method is a limitation that restricts the scalability and expandability of dictionaries. In order to overcome this limitation, we propose a novel method to automatically expand a dictionary by means of use-case analysis, which checks the validity of the unregistered word by exploring the use-cases through web crawling. The results show that the proposed method is a feasible one in terms of the accuracy of the validation process, the expandability of the dictionary and, after registration, the fast extraction time of morphemes.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.247-271
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• 2019

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.254-276
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• 2019

Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, the researchers are paying much attention to Document Summarization. The key point in any successful document summarizer is a good document representation. The traditional approaches based on word overlapping mostly fail to produce that kind of representation. Word embedding has shown good performance allowing words to match on a semantic level. Naively concatenating word embeddings makes common words dominant which in turn diminish the representation quality. In this paper, we employ word embeddings to improve the weighting schemes for calculating the Latent Semantic Analysis input matrix. Two embedding-based weighting schemes are proposed and then combined to calculate the values of this matrix. They are modified versions of the augment weight and the entropy frequency that combine the strength of traditional weighting schemes and word embedding. The proposed approach is evaluated on three English datasets, DUC 2002, DUC 2004 and Multilingual 2015 Single-document Summarization. Experimental results on the three datasets show that the proposed model achieved competitive performance compared to the state-of-the-art leading to a conclusion that it provides a better document representation and a better document summary as a result.

• Asian Journal of Business Environment
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• v.6 no.3
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• pp.21-31
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• 2016

Purpose - The purpose of this research is to determine the impact of word of mouth on customer perceived value for restaurants in Malaysia. The objectives of this research include determining how word of mouth (WoM) factors - frequency of word of mouth messages, reputation of word of mouth messenger, richness of word of mouth message, dispersion of word of mouth conversations and manner of word of mouth delivery impact customer perceived value in Malaysian restaurant industry. Research Design, Data, and Methodology - The research follows causal / explanatory research method based on quantitative data. A sample of 150 restaurant customers in Kuala Lumpur, Malaysia was selected using convenience sampling technique. Likert scale questionnaire is used to collect data and data is analysed using regression analysis through SPSS 22. Results - The statistical analysis revealed that independent variable 'manner of delivery' significantly and positively impacts customer perceived value for restaurants in Malaysia. Conclusions - To build strong positive customer perception, Malaysian restaurants can enhance word of mouth campaigns' 'manner of delivery' by making them passionate, exciting and with high emotional appeal.

• Speech Sciences
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• v.13 no.4
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• pp.143-155
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• 2006

Recently, many researchers have been interested in children with phonological disorders. The purpose of this study was to examine those children in comparison with normal children and to find better assessment criteria of the whole-word approach. Three children with phonological disorders and three normal children of 5 to 7 years old participated in the picture description tasks. Results of this study were as follows: there was a significant difference in the whole-word assessment between normal and phonological disorder children. Such criteria as whole-word correctness, whole-word complexity, whole-word intelligibility proved to be good for diagnosing children's phonological disorders. Further studies would be desirable to apply the approach to more children of various age groups.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.115-140
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• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.745-748
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• 2014

SentiWordNet is an important lexical resource supporting sentiment analysis in opinion mining applications. In this paper, we propose a novel approach to construct a Vietnamese SentiWordNet (VSWN). SentiWordNet is typically generated from WordNet in which each synset has numerical scores to indicate its opinion polarities. Many previous studies obtained these scores by applying a machine learning method to WordNet. However, Vietnamese WordNet is not available unfortunately by the time of this paper. Therefore, we propose a method to construct VSWN from a Vietnamese dictionary, not from WordNet. We show the effectiveness of the proposed method by generating a VSWN with 39,561 synsets automatically. The method is experimentally tested with 266 synsets with aspect of positivity and negativity. It attains a competitive result compared with English SentiWordNet that is 0.066 and 0.052 differences for positivity and negativity sets respectively.