• The Journal of Society for e-Business Studies
• /
• v.14 no.2
• /
• pp.1-22
• /
• 2009

As Internet shopping is getting popular, "trust" has become an important factor for customers to select websites and have repurchase intention. "Trust" has been developed from uni-dimensional concept to multi-dimensional concept in e-Commerce area. From the multi-dimensional viewpoint, this study is to investigate the processes to build trust for online stores. For this purpose, this study classifies the concept of trust into cue-based trust and experience-based trust, and then investigates their relationship in online stores. This study also identifies factors that explain cue-based trust and experience-based trust. The result from questionnaire survey distinguished cue-based trust from experience-based trust and both trust concepts are correlated each other. Second, cue-based trust is explained by perceived size, perceived reputation, and return policy, while experience-based trust is done by navigation, information usefulness and interactivity.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.1-13
• /
• 2012

3D video is regarded as the next generation contents in numerous applications. The 2D-to-3D video conversion technologies are strongly required to resolve a lack of 3D videos during the period of transition to the full ripe 3D video era. In 2D-to-3D conversion methods, after the depth image of each scene in 2D video is estimated, stereoscopic video is synthesized using DIBR (Depth Image Based Rendering) technologies. This paper proposes a novel depth fusion algorithm that integrates multiple depth cues contained in 2D video to generate stereoscopic video. For the proper depth fusion, it is checked whether some cues are reliable or not in current scene. Based on the result of the reliability tests, current scene is classified into one of 4 scene types and scene-adaptive depth fusion is applied to combine those reliable depth cues to generate the final depth information. Simulation results show that each depth cue is reasonably utilized according to scene types and final depth is generated by cues which can effectively represent the current scene.

• Journal of the Korea Convergence Society
• /
• v.3 no.1
• /
• pp.13-17
• /
• 2012

In this paper, we propose method of generation of depth map using vanishing line and texture. vanishing line is generated by parallel lines in image. For generate vanishing line, show boundary of particular angle through Gabor Filter and extract line through Hough Transform. Initial Depth Map is estimated based on vanisihng line and combine Relative Depth map that generated using Texture Cue. The proposed algorithm advanced due to combine Initial Depth Map and Relative Depth Map.

• International Commerce and Information Review
• /
• v.17 no.2
• /
• pp.41-65
• /
• 2015

Online firms collect consumers' private information, which serves as a valuable database for marketing activities. In order to encourage consumers to provide their private information, online firms offer high quality websites for consumers who provide private information. However, identity theft, phishing, and pharming, become critical social issues, consumers started to avoid providing their private information to online firms. Thus, consumers often provide false or limited information, which lacks value for practical use for the online firms. The main issue raised in this study is to discuss how online marketing activities has influence on consumers attitude and information providing behavior. From the result, this paper found that websites reputation had greatest impact on willingness of providing information. Also this study revealed that unauthorized use is the key factor for increasing distrust and avoidance of providing information.

• Journal of KIISE:Software and Applications
• /
• v.31 no.11
• /
• pp.1543-1550
• /
• 2004

Modeling from images is a cost-effective means of obtaining 3D geometric models. These models can be effectively constructed from classical Structure from Motion algorithm. However, it's too difficult to reconstruct whole scenes using SFM method since general sites contain a very complex shapes and brilliant colours. To overcome this difficulty, the current paper proposes a new reconstruction method based on a moving Planar mirror. We devise the mirror posture instead of scene itself as a cue for reconstructing the geometry That implies that the geometric cues are inserted into the scene by compulsion. With this method, we can obtain the geometric details regardless of the scene complexity. For this purpose, we first capture image sequences through the moving mirror containing the interested scene, and then calibrate the camera through the mirror's posture. Since the calibration results are still inaccurate due to the detection error, the camera pose is revised using frame-correspondence of the comer points that are easily obtained using the initial camera posture. Finally, 3D information is computed from a set of calibrated image sequences. We validate our approach with a set of experiments on some complex objects.

• Journal of Information Management
• /
• v.43 no.1
• /
• pp.109-134
• /
• 2012

This study, focusing on process of online Word-of-Mouth(oWOM) adoption in applications market which is a major issue of recent mobile industry, tried to empirically analyze how main characteristics of oWOM affect trust and process of oWOM adoption. To do this, based on understanding about applications market and precedent studies on online communication and Elaboration Likelihood Model(ELM), I developed the research model and proposed seven hypotheses. The subjects were smart phone users who ever used review in mobile applications market. The study method was questionnaire survey. As a result, trust in review was suggested as prerequisite for consumers to accept on-line review in mobile applications market. And it was empirically proved that for the customers to feel trust, these are necessary - positive assessment on argument quality, vividness of delivered explanation, and neutrality of message. The theoretical implications of this study are that based on studies on oWOM, factors affecting trust in review were explored in the environment of mobile applications market with less judgement clues for decision making compared to other on-line media and then, these factors were conceptualized. From the practical view, this study suggested implication on what attributes companies or developers can strategically utilize while investigating prerequisites of oWOM adoption.

• Korea Science and Art Forum
• /
• v.27
• /
• pp.231-246
• /
• 2017

The purpose of this study is to examine effects of sustainability of convention events on brand equity and customer loyalty. This paper also explores the mediating role of brand equity amid sustainability of convention events and customer loyalty. The four determinants ofsustainability of convention events examined in this study are economic sustainability, environmental sustainability, social sustainability and event sustainability. Brand equity refers to performance, social image, value, trust worthiness, and attachment. The findings are as follows: (1)most sustainability of convention events have a positive effect on each brand equity's elements; (2)all sustainability of convention events have a positive effect on loyalty; (3)brand equity of convention is significantly related to customer loyalty. (4)brand equity plays a mediating role between sustainability of convention and customer loyalty. The findings will not only be useful in improving the structure of sustainability of convention events, but also in enhancing competitiveness in Korea's convention industry.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.6
• /
• pp.279-290
• /
• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.