• Management & Information Systems Review
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• v.37 no.4
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• pp.175-193
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• 2018

As a new type of business model in the market competition situation of tour companies, this study has developed to the online form of the travel industry to the business form which is the combination of the electronic commerce function and the mobile service process in the provision of the simple web-site, This study explores the difficulties of change for the development of the travel industry from the point of view that recognition is not a simple marketing strategy diversification means but a change of recognition as a business model for expanding new markets or creating new markets. The factors affecting the choice of online travel agent (OTA) and the factors that influence the choice of online travel agency were analyzed. Were used for the empirical survey. The purpose of this study is to investigate the factors influencing the choice of online travel agents who have experience with or experience using online travel agency (OTA), what factors are important to them, and how they differ in importance when visiting again. The results of this study are as follows: First, there was a significant difference between the first and second visitors of online travel agencies. The results of this study were as follows: Attitude toward resolving complaints, convenience of change and cancellation, delivery of tickets and documents, convenience of complaints, The emphasis should be on establishing and strengthening service environments such as the speed of updating the latest information, the simplicity of the booking procedure, the degree of satisfaction of the past, the ability of employees to handle their work, the safety of various payment methods and settlement, The results of this study are as follows: First, the satisfaction of the online travel agency is influenced by the selection factors of the selected online tour agency, and the A/S such as the convenience of prompt delivery, Environmental factors contributed to satisfaction. It is suggested that the systematic service structure such as customer satisfaction and ease of use is a necessary marketing strategy for survival and development of online travel agencies. It is suggested that the marketing concentration strategy with the first visitors as the target market is effective and this is a part of the marketing strategy for the survival of online travel agencies.

• Broadcasting and Media Magazine
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• v.11 no.4
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• pp.104-117
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• 2006

In this Paper, we analyze the application of Interactive Data Broadcasting in DMB(Digital Multimedia Broadcasting) in the accordance with convergence of service and technology. With the acceleration of digital convergence in the Ubiquitous period substantial development of digital media technology and convergence of broadcasting and telecommunication industry are being witnessed. Consequently these results gave rise to newly combined-products such as DMB(Digital Multimedia Broadcasting), WCDMA(Wide-band code division multiple access), Wibro(Wireless Broadband Internet), IP-TV (Internet protocol TV) and HSDPA(High speed downlink packet access). The preparatory stage for the implementation of Interactive Data Broadcasting Service will be reached by the end of December, 2006. DMB is the first result of a successful convergence service between Broadcasting and Telecommunication in new media era. Multimedia technology and services are the core elements of DMB. The Data Broadcasting will not only offer various services of interactive information such News, Weather, Broadcasting Program etc, but also be linked with characteristic function of mobile phone such as calling and SMS(Short Message Service) via Return Channel.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Spatial Information Research
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• v.23 no.6
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• pp.57-66
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• 2015

Recently, the utilization of geospatial open platforms has been constantly increased and the interest in 3D geospatial data such as terrain, building and shopping mall has been increased significantly. In particular, rather than simplified 3D geospatial data, interest in high-precision 3D geospatial data which similarly represents the real world objects has increased significantly. In order to satisfy the demand for such the high-precision 3D geospatial data, various kinds of 3D geospatial open platforms has been developed and has provided services on the web. However, most of the 3D geospatial open platforms have been used plug-in module in order to ensure a fast 3D rendering performance on the web, despite the many problems such as difficulty of the installation, no supporting of cross browser/operating system and security issues. In addition, recently, the existing 3D geospatial open platforms based on plug-in module are facing a serious problem, by declaring the NPAPI service interruption in Chrome and Firefox browsers. In this study, we presents the design and implementation of a new 3D geospatial open platform based on HTML5/WebGL technology without the use of plug-ins. Such the new 3D geospatial open platform based on HTML5/WebGL may support cross browsers such as IE, Chrome, Firefox, Safari and cross OS platforms such as Windows, Linux, Mac and mobile OS platforms.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.23-31
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• 2020

The need for personalized recommendation is growing due to convenient access and various types of items due to the development of information communication and smartphones. Weather and weather conditions have a great influence on the decision-making of users' places and activities. This weather information can increase users' satisfaction with recommendations. In this paper, we propose a collaborative filtering-based place recommendation system using living index by utilizing living index of users' location information on mobile platform to find users with similar propensity and to recommend places by predicting preferences for places. The proposed system consists of a weather module for analyzing and classifying users' weather, a recommendation module using collaborative filtering for place recommendations, and a management module for user preferences and post-management. Experiments have shown that the proposed system is valid in terms of the convergence of collaborative filtering algorithms and living indices and reflecting individual propensity.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.586-596
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• 2011

In the IT industry, processing units of IT applications are getting smaller and high efficient. Furthermore, the realization of various smart functions is highly feasible now due to advances in sensing technology. The service infrastructures on high efficient and compact mobile devices are applied to various areas. These also could be possessed by users and is built into the devices. Currently, studies on the UX(User Experience) field to attempt an analysis and prediction of user's information are continuing with reference to the UI(User Interface). However, research on the common framework of classification and storing the user-information, and standardization of form has not been attempted yet. In this study, we proposed the AUX(Associative user Experience) model and process structure to store various empirical data by users. The AUX model expressed a diversity of user's empirical data using extended E-TCPN model. And also, we expressed the data structure using XML with reference to the application of AUX model. This expressed model and separation of process structure guarantee its specialty, productivity and flexibility through the humanistic characteristics of users and the independence of technical process structure. The AUX model maps out the AUX information process architecture and expressed the process with the improved MPP algorithm, to analyze of its performance. The simulation of movements applying to MPP traffic allocation of VOD is used to analyze of its performance. The playback deviation of MPP Graphic Allocation Algorism where the AUX model was applied was improved by 10.41% more than the one where it was not applied. As a result of that, playback performance has improved due to the conversion of AUX with accessing media, content of users and dynamic traffic allocation such as MPI and CPI.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.64-69
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• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.3-8
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• 2011

Recently, the demand for enterprise for service map providing and portal site services of a 3D virtual city model for public users has been expanding. Also, accuracy of the data, transfer rate and the update for the update for the lapse of time emerge are considered as more impertant factors, by providing 3D information with the web or mobile devices. With the latest technology, we have seen various 3D data through the web. With the VRML progressing actively, because it can provide a virtual display of the world and all aspects of interaction with web. It offers installation of simple plug-in without extra cost on the web. LiDAR system can obtain spatial data easily and accurately, as supprted by numerous researches and applications. However, in general, LiDAR data is obtained in the form of an irregular point cloud. So, in case of using data without converting, high processor is needed for presenting 2D forms from point data composed of 3D data and the data increase. This study expresses urban LiDAR data in 3D, 2D raster data that was applied by compressing algorithm that was used for solving the problems of large storage space and processing. For expressing 3D, algorithm that converts compressed LiDAR data into code Suited to VRML was made. Finally, urban area was expressed in 3D with expressing ground and feature separately.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.67-75
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• 2015

According to the changes of the mobile environments, the usage and interest of the Android apps have been increased. But the usage of illegally-copied apps has been also increased. And the transparency and dependability of the app markets has been decreased. Therefore there are many cases for the copyright infringement of app developers. Although several methods for preventing illegally-copied apps have been studied, there may exist possible ways to bypass the methods. Since it is difficult to find out the first distributors of the illegally-copied apps, it is not easy to punish them legally. This paper proposes the method of detecting illegally-copied apps. The proposed detector can detect the illegally-copied apps using odex file, which is created when the app is installed. The detector can also find out the information of the first distributors based on forensic watermark technique. Since the illegally-copied app detector is running as a service on the system server, it is granted that the detector hides from the users. As an experiment result, the illegally-copied app detector takes on average within 0.2 seconds to detect and delete an illegally-copied app.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.61-76
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• 2018

Everything is coming into the world of network where modern people are living. The Internet of Things that attach sensors to objects allows real-time data transfer to and from the network. Mobile devices, essential for modern humans, play an important role in keeping all traces of everyday life in real time. Through the social network services, information acquisition activities and communication activities are left in a huge network in real time. From the business point of view, customer needs analysis begins with SNS data. In this research, we want to build an automatic collection system of SNS contents of web environment in real time using Python. We want to help customers' needs analysis through the typical data collection system of Instagram, Twitter, and YouTube, which has a large number of users worldwide. It is stored in database through the exploitation process and NLP process by using the virtual web browser in the Python web server environment. According to the results of this study, we want to conduct service through the site, the desired data is automatically collected by the search function and the netizen's response can be confirmed in real time. Through time series data analysis. Also, since the search was performed within 5 seconds of the execution result, the advantage of the proposed algorithm is confirmed.