• Asia pacific journal of information systems
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• v.26 no.4
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• pp.577-592
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• 2016

The proliferation of mobile applications and the unique characteristics of the mobile environment have attracted significant research interest in understanding customers' purchasing behaviors in mobile commerce. In this study, we extend customer value theory by combining the predictors of product performance with customer value framework to investigate how in-store information creates value for customers and influences mobile application downloads. Using a data set collected from the Google Application Store, we find that customers value both text and non-text information when they make downloading decisions. We apply latent semantic analysis techniques to analyze customer reviews and product descriptions in the mobile application store and determine the embedded valuable information. Results show that, for mobile applications, price, number of raters, and helpful information in customer reviews and product descriptions significantly affect the number of downloads. Conversely, average rating does not work in the mobile environment. This study contributes to the literature by revealing the role of in-store information in mobile application downloads and by providing application developers with useful guidance about increasing application downloads by improving in-store information management.

• Smart Structures and Systems
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• v.16 no.1
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• pp.47-65
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• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.559-564
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• 2006

The purpose of this study is to minimize negative effect of VMS travel time information service by sensitivity analysis, which forecasts the change in link traffic volume. As a result, strategies for providing travel information that can change driving patterns for minimizing travel time were found. The framework for analysis is recently expanded with the application of game theory. According to the experiment, the algorithm generated for travel time information service reduces total travel time and yields travel patterns that is very close to the system optimization. Also, this study found that the route the travel time service information is provided about could play the important role.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.51-70
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• 2011

This paper introduces a new credit card payment scheme called No Number Credit Card that can significantly reduce the possibility of credit card fraud. The proposed payment system is loosely based on Kerberos, a cryptographic framework that has stood the test of time. In No Number Credit Card, instead of card numbers, only payment tokens are exchanged between the customers and merchants. The tokens are generated based on the payment amount, payment type, client information, and merchant information. However, it does not contain the credit card number, so the merchant or a database hacker cannot acquire and illegally use any credit card numbers. The No Number Credit Card system is ideal for online e-commerce transactions and can be used with any credit card that users possess. It can be used with minor modifications to the current card payment system. We provide the principles of its operation through scenario analysis, a sample implementation, and a security analysis

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.281-282
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• 2019

In recent years welfare of animals is the biggest challenge because animals, especially dogs are widely recognized as pet as well as they are using as service animals. So, for the wellbeing of the dog it is necessary to perform objective assessment to track their behavior in everyday life. In this paper, we have proposed an automatic behavior assessment system for dogs based on a neck worn and tail worn accelerometer and gyroscope platform, and data analysis techniques that recognize typical dog activities. We evaluate the system based on the analysis of 8 behavior traits in 3 dogs, incorporating 2 breeds of various sizes. Our proposed framework able to reproduce the manual assessment that is based on the video recording which is treated as gold standard that exhibits the real-life use case of automated dog behavior analysis.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.3-15
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• 2020

For a successful construction project, the requirements of the client should be clearly defined and this should be reflected in the project based on the expertise of each project participant throughout the entire life-cycle. Therefore, it is necessary to establish the concept of Requirements Management to systematize and manage project requirements in terms of information management. This study aims to comprehensively define the concept of requirements management in the architecture industry and to provide a methodological basis for efficiently managing design requirements information by suggesting category of requirements information type and information analysis criteria. In addition, based on the case study, the requirements information was analyzed to propose a systemization methods of requirements management for PMO' design management and information management.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.702-705
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• 2006

Because of explosive increase of information, it spends a lot of time to trace and analysis research trends during total R&D process. It has rapidly evolved from R&D or process development within a specific domain of knowledge to R&D or process development through knowledge convergency. To accept such a paradigm, it is necessary to convert dissemination system from a separate, standalone, and fragmentary information to highly coupled fusion information. Although there are several studies on knowledge flows between science and technology or technology and industry, it is difficult to analyse and utilize quantitatively to establish policy of Science, Technology, and Industry. The reason is the lack of information resource to analyse knowledge flow from science to industry. This paper intends to develop framework of highly coupled linking system between patent and scientific paper to utilize R&D, S&T policy, and industry policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.135-158
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• 2003

The Purpose of this study is to investigate how information use contributes to learning. Conducted as part of a larger study, this study focuses on learning by analyzing students' use of cognitive skills during the Process of using information. Within the broad methodological framework of qualitative research in constructivist paradigm (Guba and Lincoln, 1998), the study applied the revised Bloom's taxonomy (Anderson and Krathwohl, 2000) as a particular framework to understand the Phenomenon. Participants included 21 high school juniors in an honors' class of persuasive speech. The study's combinational use of two techniques -concept mapping and individual interview - in a naturalistic setting Proved to be the unique methods for researching the reflection of information use in learning Products. The results revealed that changes in students' understanding occured in four types - simple, analytic, organizational, and holistic changes. The analysis using the revised Bloom's taxonomy showed that a variety of cognitive skills were used during the whole process of information use and that the use of higher levels of cognitive skills is particularly crucial.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.