• KIISE Transactions on Computing Practices
• /
• v.21 no.2
• /
• pp.101-108
• /
• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• Journal of KIISE:Databases
• /
• v.41 no.4
• /
• pp.226-241
• /
• 2014

LOD(Linked Open Data) is composed of RDF triples which are based on ontologies. They are identified, linked, and accessed under the principles of linked data. Publications of LOD data sets lead to the extension of LOD cloud and ultimately progress to the web of data. However, if ontologically the same things in different LOD data sets are identified by different URIs, it is difficult to figure out their sameness and to provide trustworthy links among them. To solve this problem, we suggest a Trustworthiness Improving Link Evaluation, TILE for short, technique. TILE evaluates links in 4 steps. Step 1 is to consider the inference property of syntactic elements in LOD data set and then generate RDF triples which have existed implicitly. In Step 2, TILE appoints predicates, compares their objects in triples, and then evaluates links between the subjects in the triples. In Step 3, TILE evaluates the predicates' syntactic property at the standpoints of subject description and vocabulary definition and compensates the evaluation results of Step 2. The syntactic elements considered by TILE contain RDFS, OWL, OWL2 which are recommended by W3C. Finally, TILE makes the publisher of LOD data set review the evaluation results and then decide whether to re-evaluate or finalize the links. This leads the publishers' responsibility to be reflected in the trustworthiness of links among the data published.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.85-107
• /
• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Spatial Information Research
• /
• v.20 no.2
• /
• pp.129-136
• /
• 2012

Recently international organizations such as ISO/TC211, OGC, INSPIRE (Infrastructure for Spatial Information in Europe) make an effort to share geospatial data using semantic web technologies. In addition, smart phone and social networking services enable community-based opportunities for participants to share issues of a social phenomenon based on geographic area, and many researchers try to find a method of extracting issues from that. However, serviceable spatial ontologies are still insufficient at application level, and studies of spatial information extraction from SNS were focused on user's location finding or geocoding by text mining. Therefore, a study of extracting spatial phenomenon from social media information and converting it into geosemantic knowledge is very usable. In this paper, we propose a framework for extracting keywords from micro-blog, one of the social media services, finding their relationships using data mining technique, and converting it into spatiotemopral knowledge. The result of this study could be used for implementing a related system as a procedure and ontology model for constructing geoseem antic issue. And from this, it is expected to improve the effectiveness of finding, publishing and analysing spatial issues.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1480-1484
• /
• 2003

This paper presents the design and development of network for housing estate security system. The system can cover up to 961 houses which can be up to 1,200 meters long transfer rate of 9,600 bps. This system uses checking and warning the abnormal situation. More over this system has ability to control switch on/off the electrical equipment in the house via AC line control system. The system consists of 4 parts. The first part is a security system of each house using MCS-51 microcontroller as a central processing unit scan 32 sensors and control 8 appliances and send alarm. The MCS-51 microcontroller received control signal via telephone used DTMF circuit. The second part is distributed two levels master/slave network implementing after RS-485 serial communication standard. The protocol its base on the OSI (Open Systems Interconnection) 7 layers protocol model design focus on speed, reliability and security of data that is transferred. The network security using encrypt by DES algorithm, message sequence, time stamp checking and authentication system when user to access and when connect new device to this system. Flow control in system is Poll/Select and Stop-and-Wait method. The third part is central server that using microcomputer which its main function are storing event data into database and can check history event. The final part is internet system which users can access their own homes via the Internet. This web service is based on a combination of SOAP, HTTP and TCP/IP protocols. Messages are exchanged using XML format [6]. In order to save the number of IP address, the system uses 1 IP address for the whole village in which all homes and appliance in this village are addressed using internal identification numbers. This proposed system gives the data transfer accuracy over 99.8% and maximum polling time is 1,120 ms.

• Journal of Digital Convergence
• /
• v.18 no.6
• /
• pp.373-378
• /
• 2020

For improving interoperability of medical information, health level 7 has initiated the development of a next-generation framework for the exchange of medical information called the Fast health interoperability resources (FHIR). However, there was no attempt to exchange the medical three-dimensional (3D) image with clinical data via FHIR. Thus, we designed a new method. The 3D image to be made from computed tomography was converted to the javascript object notation (JSON) file format, and clinical data was added. We made a test FHIR server, and the client used the postman. The JSON file was attached to the body, and was then transmitted. The transmitted 3D image could be seen through a web browser, and attached clinical data was identified in the source code. This is the first attempt to exchange the medical 3D image. Additional researches will be needed to develop applications or FHIR resources that apply this method.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.10 no.1
• /
• pp.76-83
• /
• 2011

The IEEE WAVE-based communication systems do not provide handover services since most of the application layer messages of a small amount containing text data that are related to safe driving. Multimedia data service such as web pages and CCTV video clips, however, require a seamless handover for continuation of a session via multiple RSUs. In this paper, we propose a new proactive handover protocol based on IEEE WAVE. According to the proposed handover protocol, the OBU notifies the old RSU of its departure from the coverage such that the old RSU forwards to the new RSU the data heading towards the OBU to be cached for the further delivery upon its entry into the new RSU's coverage. The simulation results are presented which shows the performance of the proposed protocol in terms of throughput, delivery ratio and handover delay.

• Journal of Cadastre & Land InformatiX
• /
• v.46 no.2
• /
• pp.211-224
• /
• 2016

Based on the 'Government 3.0', the government opens the public data and encourages the active use in the private sector. Recently, the spatial and statistical information that is one of the public data is being widely used in the various web business as a high value-added information. In this study, we propose an architecture of high-availability, high-reliability and high-performance open platform which can provide a variety of services such as searching, analysis, data mining, and thematic mapping. In particular, we present two different system architectures for the government and the public services, by reflecting the importance of the information security and the respective utilization in the private and public sectors. We also compared a variety of server architecture configurations such as a clustered server configuration, a cloud-based virtual server configuration, and a CDN server configuration, in order to design a cost- and performance-effective spatial-statistical information open platform.

• Journal of Korea Multimedia Society
• /
• v.12 no.11
• /
• pp.1629-1639
• /
• 2009

This paper describes the environmental monitoring system for supporting comfortable subways based on USN. Our development system includes the sensor field based on integrated sensor, monitoring system for supporting the local and remote monitoring and middle-ware performs the collecting, analyzing, and storing the data. In this paper, we installed the temperature, humidity, micro-dust sensor and water-level sensor for supporting the rail-roads and make up the integrated sensor enables to reuse the analog device from 4~20mA output with connection of wireless sensor device. Middleware includes the modules of collecting, analysis, and storing the data and monitoring system supports the local for administrator and remote monitoring for citizen services based on web. The middleware and monitoring in this paper is comprised of some components can reuse and support the change of application and sensors. Our development system supports the mobility of sensor devices and distributes system. Data collection and management function supported by middleware will use assessment.

• The KIPS Transactions:PartD
• /
• v.10D no.4
• /
• pp.603-612
• /
• 2003

According to development of Web, an amount of XML documents has been increasing. So, many researches are proceeding to verify XML data coming from clients and to store or query efficiently database. In order to verify, store and query, DTD or XML Schema of XML documents is necessary. However, Schemaless XML documents couldn't be operated since they do not have either DTD or in Schema. In this paper, we extract XML schema in order to verify XML data and store or query efficiently database from either well-formed XML or XML Schemaless documents. XML Schema extracting technique which is proposed in this paper extract Schema graph using simulation and dataguide that is a extracting technique for semistructured characteristics of XML data. Also, we propose extracting technique for XML Schema using pattern tables that are considerated with Schema graph and reusability.