• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3138-3150
• /
• 2021

Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.5
• /
• pp.67-72
• /
• 2019

The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

• Information Systems Review
• /
• v.25 no.2
• /
• pp.1-30
• /
• 2023

This study analyzes and examines the travel behavior of Chinese people in Korea through a questionnaire survey of Chinese people who are long-term residents in Korea using Xiaohongshu App (RED). In this study, we add some variables to the MTEs (Memorable Tourism Experiences) model to analyze the travel behavior of Chinese people who are in Korea for a long period of time. We also chose to survey the users of Xiaohongshu App (RED), a popular software in recent years, and found the following findings in 240 valid questionnaires: (1) Scenery, Entertainment, and Informativeness have positive effects on people sharing travel experiences, while interaction does not. (2) Sharing travel experiences had a positive effect on travel satisfaction and the intention to go to other destinations, and travel satisfaction had a positive effect on the intention to go to other destinations. This paper extends the literature on tourism by combining MTEs and UGC (User-Generated Content) models, and also provides relevant suggestions for further research on the travel behavior of foreigners in Korea.

• Journal of Smart Tourism
• /
• v.1 no.2
• /
• pp.19-25
• /
• 2021

Before COVID-19, tourist destinations have experienced problems with congestion of both famous tourist attractions and public transportation. Over-tourism is not an issue at this time, but it is likely to rekindle after the COVID-19 pandemic ends. One method of mitigating over-tourism is to estimate tourist behavior using a tourist transition model and consequently adjust public transportation operations. In this study, we propose a construction method for a model of tourist transitions among tourist attractions based on tourist GPS trajectory data. We construct tourist transition models using actual trajectory data for tourists staying in the vicinity of Kyoto City. The results verify the model performance.

• Journal of Smart Tourism
• /
• v.2 no.1
• /
• pp.5-19
• /
• 2022

Smart tourism is seen as a revolution in the tourism industry, involving innovative and transformative theoretical-practical approaches for the sector. As a result of its application in the tourist context, benefits can be seen such as more sustainable practices, greater mobility and better accessibility in destinations, evolution of processes and experiences of tourists. Much of this is achieved through the support of technological solutions. However, despite the immense expectations, and the many researches carried out on it, a literature summary regarding the dimensions that can be observed in each application of this smart tourism has not yet been proposed. Therefore, supported by the PRISMA recommendation, this research proposed to carry out an integrative review of the literature on smart tourism (in its different levels of application, such as the city, the destination and the smart tourism region), with the objective of mapping the dimensions that underlie it. Thus, from an initial scope of 833 intellectual productions obtained, inputs were found for the dimensions in 363 of them after a thorough analysis. The compilation of data obtained from these productions supported the proposition of 14 operational dimensions of smart tourism, namely: collaboration, technology, sustainability, experience, accessibility, knowledge management, innovation management, human capital, marketing, customized services, transparency, safety, governance and mobility. With this set of dimensions, it is envisaged that the implementation of smart tourism projects can present more comprehensive and assertive results. In addition, shortcomings and opportunities for new research that support the evolution of the theory and practice of smart tourism are highlighted.

• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.437-448
• /
• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Asia pacific journal of information systems
• /
• v.29 no.3
• /
• pp.448-467
• /
• 2019

In a new age of smart tourism, free independent travelers (FITs) choose their travel routes in a more diversified and less predictable way with the aid of smart services. This paper focuses on the movements of Chinese outbound FITs in the U.S. in the year of 2018. 110 places to visit (destinations) extracted from 122 travel routes recommendations on Qyer.com, a major online travel community in China, are analyzed with social network analysis (SNA). Based on the results of SNA, employing degree centrality, eigenvector centrality, betweenness centrality, network visualization, and cluster diagram methods, some preferred cities and natural attractions outside city centers (i.e., New York City (NYC), Los Angeles, San Francisco, Washington D.C., and Niagara Falls) are identified. Moreover, it is found that NYC in the East and Los Angeles in the West play a major role in the movements of Chinese FITs. This study contributes to the body of knowledge on tourist destination movements and provides valuable implications for smart service development in the tourism and hospitality industry.

• The Journal of Information Systems
• /
• v.27 no.3
• /
• pp.203-225
• /
• 2018

Purpose This study investigated the impact of review language style (affective vs. cognitive) on review helpfulness and the moderating effects of the types of attractions in the relationships between the review language and its helpfulness. Design/methodology/approach This study investigates the impact of review language style (affective vs. cognitive) on review helpfulness and the moderating effects of the types of attractions in the relationships between the review language and its helpfulness. This study selected two hedonic and utilitarian attractions (Hedonic: Brandenburg Gate, Utilitarian: Peragamon Museum) located in Berlin. A total of 3,320 reviews was collected from TripAdvisor. We divided online reviews posted for these places into reviews with more affective language and with more cognitive language by using the LIWC. Then, we investigated the impact of language effect on review helpfulness across the attraction type. Findings The findings suggest that peers tend to judge more helpful toward cognitive language in attraction reviews regardless of attraction type. This study found that peers tend to perceive more helpful toward cognitive review in utilitarian attractions. Even though there was an interaction effect between review language and attraction type, in hedonic attractions, the influence of cognitive language was reduced, but still cognitive reviews would get more helpful votes.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.6
• /
• pp.49-55
• /
• 2017

Robots, games and life applications have been developed while computer areas are developed. Moreover, various applications have been utilized for various users including the early childhood. Recently, smart phones have been dramatically used by various users including early childhood. Many applications need to find a path from a starting point to destinations. For example, without using real maps, users can find the direct paths for the destinations in realtime. Specifically, path exploration in game programs is so important to have accurate results. Nowadays, with these techniques, diverse applications for educations of early childhood have been developed. To deal with the functions, necessity of efficient path search programs with high accuracy becomes much higher. In this paper, we design and develop a friendly maze program for early childhood based on a path searching algorithm. Basically, the path of lineal distance from a starting location to destination is considered. Moreover, weight values are calculated by considering heuristic weighted h(x). In our approach, A* algorithm searches the path considering weight values. Moreover, we utilize depth first search approach instead of breadth first search in order to reduce the search space. so it is proper to use A* algorithm in finding efficient paths although it is not optimized paths.

• Knowledge Management Research
• /
• v.23 no.1
• /
• pp.133-148
• /
• 2022

In an ever-changing tourism environment, we need to think about how to successfully attract tourists and provide them with memorable experiences. Smart tourism content is considered as a useful tourism resource for converting into an attractive tourist destination by providing new values in various tourist destinations as well as the changed tourism patterns due to COVID-19. However, there are still few successful cases of smart tourism contents that have secured economic sustainability. Accordingly, this study applied the Contingent Valuation Method (CVM) to estimate the economic value perceived by tourists for smart tourism contents based on augmented reality to develop a smart tourism content development plan that can secure economic sustainability. As a results, it was confirmed that the lower the offered amount, the higher the awareness of the new value, the higher the likelihood of willingness to pay. Based on these research results, this study presented academic and practical implications for the development of smart tourism content that secured economic sustainability.