• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.436-453
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• 2022

This study aims to investigate the effects of fashion information search and innovativeness of consumers on service quality of image search. Furthermore, it focuses on exploring the effect of image search service quality on use intention. Data of mobile-friendly consumers in their 20s and 30s was collected in September 2021 via an online survey. Finally, 300 samples were used for the data analysis. First, motivation for information search in fashion was divided into four factors: information, relation, leisure, and entertainment motivation. Furthermore, service quality of image search was divided into four factors: accuracy, convenience, customization, and aesthetics. Second, regression analysis was conducted to evaluate the effect of fashion information search motivation on service quality. As a result, it was found that information, relation, and entertainment motivation except leisure motivation had significant effects on all factors of service quality. Third, fashion innovativeness had no significant effect on aesthetics while consumer innovativeness significantly influenced all factors of service quality. Fourth, accuracy, convenience, and aesthetics had a significant effect on use intention.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.75-84
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• 2006

With considering center-biased characteristic, NTSS(New Three-Step Search Algorithm) can improve the performance of TSS(Three-Step Search Algorithm) which is one of the most popular fast block matching algorithms(BMA) to search a motion vector in a video sequence. Although NTSS has generally better Quality than TSS for a small motion sequence, it is hard to say that NTSS can provide better quality than TSS for a large motion sequence. It even deteriorates the quality to increase a search window size using NTSS. In order to address this drawback, this paper aims to develop a new adaptive window size-based three step search scheme, called AWTSS, which can improve quality at various window sizes in both the small and the large motion video sequences. In this scheme, the search window size is dynamically changed to improve coding efficiency according to the characteristic of motion vectors. AWTSS can improve the video quality more than 0.5dB in case of large motion with keeping the same quality in case of small motion.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.885-888
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• 2000

Among the previous searching methods, there are the typical methods such as full search and three-step search, etc. Block motion estimation using exhaustive search is too computationally intensive. To apply in practice, recently proposed fast algorithms have been focused on reducing the computational complexity by limiting the number of searching points. According to the reduction of searching points, the quality performance is aggravated in those algorithms. In this paper, We present a fast and efficient search algorithm for block motion estimation that produces better quality performance and less computational time compared with a three-step search (TSS). Previously the proposed Two Step Search Algorithm (TWSS) by Fang-Hsuan Cheng and San-Nan sun is based on the ideas of dithering pattern for pixel decimation using a part of a block pixels for BMA (Block Matching Algorithm) and multi-candidate to compensate quality performance with several locations. This method has good quality performance at slow moving images, but has bad quality performance at fast moving images. To resolve this problem, the proposed algorithm in this paper considers spatial and temporal correlation using neighbor and previous blocks to improve quality performance. This performance uses neighbor motion vectors and previous motion vectors in addition, thus it needs more searching points. To compensate this weakness, the proposed algorithm uses statistical character of dithering matrix. The proposed algorithm is superior to TWSS in quality performance and has similar computational complexity

• Journal of Distribution Science
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• v.20 no.5
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• pp.49-64
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• 2022

Purpose: This research aims to determine the quality of online store designs that make consumers who use online market board applications have the urge to make impulse buying. This research was conducted because impulse buying is the most common buying behavior. Research design, data and methodology: This research used non-probability sampling. The sample size was 195 respondents from the distribution and service industries by applying a purposive sampling technique. The data collection technique employed a questionnaire distributed online according to predetermined criteria: mobile device users who accessed the online market board application and made at least one purchase in the last six months. The data analysis method utilized was structural equation modeling (SEM). Results: The findings revealed that usability, functionality, and sociability factors affected hedonic and utilitarian search. Furthermore, these findings proved that hedonic search affected impulse buying drives. In contrast, the utilitarian search did not affect impulse buying drives. Conclusions: The usability, functionality, and sociability factors supported hedonic and utilitarian searches. Consumer information security increased consumer confidence in an online store because it was considered to protect matters related to their privacy. The hedonic search also increased impulse buying drives. Consumers prefer to use their spare time to search through online market board applications, which provide many attractive promos.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.43-45
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• 2000

For motion estimation, the block matching algorithm is widely used to improve the compression ratio of low bit-rate motion video. As a newly developed fast search algorithm, the nearest-neighbors search technique has a drawback of degrading video quality while providing fisher speed in search process. In this paper, a modified nearest-neighbors search algorithm is proposed in which a double rectangular shaped search-candidate area is used to improve video quality in encoding process with a small increasing of search time. To evaluate the proposed algorithm. other methods based on the nearest-neighbors search algorithm are investigated.

• The Research Journal of the Costume Culture
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• v.10 no.3
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• pp.261-269
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• 2002

The purposes of this study were to investigate component of service quality and to determine significant factors on the service quality and buying intention of internet apparel shopping mall. The data were collected from 212 female adults using questionnaire. Using SPSS package, Cronbach's α, factor analysis, and multiple repression analysis were performed. The results could be summarized as follows. 1. The service quality of internet apparel shopping mall was perceived as reliability, advantage, responsibility, product assortment, tangibles, and rapidness. 2. For perceived risk, privacy risk, economic risk, delivery risk, size risk, and quality risk were investigated. The perceived risk except economic risk and web search ability had an effect on the service quality of internet apparel shopping mall. 3. The most of perceived risk, web search ability, and advantage of the service quality had an effect on the shopping intent of the internet apparel shopping mall. Based on the these results, marketing strategies were suggested.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.246-247
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• 2010

This paper proposes a fast motion estimation algorithm based on motion speed and multiple initial center points. The proposed method predicts initial search points by means of the spatio-temporal neighboring motion vectors. A dynamic search pattern based on motion speed and the predicted initial center points is proposed to quickly obtain the motion vector. Due to the usage of the spatio-temporal information and the dynamic search pattern, the proposed method greatly accelerates the search speed while maintaining a good predicted image quality. Experimental results show that the proposed method has a good predicted image quality in terms of PSNR with less search time as compared to the Full Search, New Three-Step Search, and Four-Step Search.

• Journal of the Korea Safety Management & Science
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• v.3 no.1
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• pp.67-79
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• 2001

This study is based on Parasuraman, Zeithaml 8l Berry［19］`s SERVQUAL measure that develop for estimation of service quality, so this study proposes the present condition of customer service and improvement method on internet search engine. This study also develops a questionnaire for analyzing customer satisfaction considering the present condition of internet service. We're going to analyze the customer service quality that classified by search engines, service quality with university students who use usually internet.