• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.265-273
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• 2012

It is essential to have Context-aware technology for personalization recommendation services and the appropriate representation and definition of Context information for context-aware. Ontology is possible to represent knowledge freely and knowledge can be extended by inferring. In addition, design of the ontology model is needed according to the purposes of utilization. This paper used context-aware technologies to implement a user personalization recommendation service. It also proposed the context through OWL modeling for user personalization recommendation service and used inference rules and inference engine for context reasoning.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.857-866
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• 2003

For detecting an intrusion based on the anomaly of a user's activities, previous works are concentrated on statistical techniques in order to analyze an audit data set. However. since they mainly analyze the average behavior of a user's activities, some anomalies can be detected inaccurately. In this paper, a new clustering algorithm for modeling the normal pattern of a user's activities is proposed. Since clustering can identify an arbitrary number of dense ranges in an analysis domain, it can eliminate the inaccuracy caused by statistical analysis. Also, clustering can be used to model common knowledge occurring frequently in a set of transactions. Consequently, the common activities of a user can be found more accurately. The common knowledge is represented by the occurrence frequency of similar data objects by the unit of a transaction as veil as the common repetitive ratio of similar data objects in each transaction. Furthermore, the proposed method also addresses how to maintain identified common knowledge as a concise profile. As a result, the profile can be used to detect any anomalous behavior In an online transaction.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.249-252
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• 2001

This paper focuses on the consideration of not only QoS parameters in wired network, but also QoS parameters in wireless network that supported for the Efficient QoS in the Al1 Service Levels. So, We supposed the "Efficient QoS Model" that guaranteed the QoS parameters "Loss Profile" , "Service Degradation" , "Latency and Jittering" , "Mobility of Mobile User" , "Probability of seamless communication" in wired-wireless networks. And the Method of Efficient QoS support that we supposed consists of "Multicast Routing-RSVP Protocol architecture based on Mobile IP" and "Protocols internetworking model ".

• Journal of Information Technology Services
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• v.20 no.3
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• pp.57-73
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• 2021

Recently, online job websites have been activated as unemployment problems have emerged as social problems and demand for job openings has increased. However, while the online job platform market is growing, users have difficulty choosing their jobs. When users apply for a job on online job websites, they check various information such as job contents and recruitment conditions to understand the details of the job. When users choose a job, they focus on various details related to the job rather than simply viewing and supporting the job title. However, existing online job websites usually recommend jobs using only quantitative preference information such as ratings. However, if recommendation services are provided using only quantitative information, the recommendation performance is constantly deteriorating. Therefore, job recommendation services should provide personalized services using various information about the job. This study proposes a recommended methodology that improves recommendation performance by elaborating on qualitative preference information, such as details about the job. To this end, this study performs a topic modeling analysis on the job content of the user profile. Also, we apply LDA techniques to explore topics from job content and extract qualitative preferences. Experiments show that the proposed recommendation methodology has better recommendation performance compared to the traditional recommendation methodology.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.264-271
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• 2013

A method of multiple transport-aircraft mission modeling is proposed in order to improve the efficiency of evaluating and optimizing pre-mission plans. To deal with the challenge of multiple transport-aircraft missions, the object-oriented modeling method is utilized. The elements of the mission are decomposed into objects and businesses, And the major mission objects and their important properties are summarized. A complex mission can be broken down into basic business modules such as the ground section and flight section. The business models of loading and fueling services in the ground section are described. The business model of the flight section is composed of an air route and flight profile with the flight equation and the fuel consumption model. The logical relationship of objects and business modules is introduced. The architecture of the simulation system, which includes a database, computation module, graphical user interface (GUI) module, and a result analysis module, is established. A sample case that includes two different plans is provided to verify the model's ability to achieve multi-aircraft composite mission simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.901-904
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• 2014

As sensing techniques have advanced, context-aware technologies have been developed under the various domain for each different purpose. The number of services were created and are being used actually, but the services for specific spatial domain are not adequate yet. To solve this, there have been many efforts, and some of them were actually successful. Among them, the methods which used ontology-based inference were relatively reliable and appropriate for context-aware system, but not able to support contexts for individual without complex rules. In this paper, current scope of context inference is extended from user-oriented context modeling to entity-oriented. Furthermore, we used user profile and home profile to provide more specific context information of not only each individual but entity.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.175-184
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• 2008

To construct user profiles automatically, an extraction method for representative keywords from a set of documents is needed. In our previous works, we suggested such a method and showed its usefulness. Here, we apply it to the classification problem and observe how much it contributes to performance improvement. The method can be used as a linear document classifier with few modifications. So, we first evaluate its performance for that case. The method is also applicable to some non-linear classification methods such as GIS (Generalized Instance Set). In GIS algorithm, generalized instances are built from training documents by a generalization function and then the K-NN algorithm is applied to them, where the method can be used as a generalization function. For comparative works, two famous linear classification methods, Rocchio and Widrow-Hoff algorithms, are also used. Experimental results show that our method is better than the others for the case that only positive documents are considered, but not when negative documents are considered together.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.314-324
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• 2004

Recently, high-speed internet subscribers have grown continuously, and reached up to 10 millions. But existing network management that is responsible only for user access is confronted with many difficulties, since user access network(xDSL, Cable, B-WILL, and so on) has diversified and value added wired/wireless contents service has developed. In this paper propose the Agent based Inter Networking platform as object-oriented hierarchical system that can provide various service such as access QoS(Quality of Service), customized application service and security service according to user on demand. This system has divided into two parts(user agent and agent management system ＆ local and central management systems). Management system periodically receive status information such as bandwidth, download speed, delay, current service, and so on, and process them, then build a policy based on processed information. According to personal user profile that is generated by this policy, the customized service can be provided for users. And This system adopt the object-oriented modeling in case that system migration and integration, and implement a system that is robust and stable for security through hierarchical server system.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.9-18
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• 2008

Research is being made for users' convenient access to services such as personalized data and contents services. The use of information and the fusion of services in various devices and terminals suggest the necessity to know what personalization mechanism is used to provide high quality contents at a time and place desired by users. Existing mechanisms are not easy to be handled by other service providers because each service provider has different preference and personal information, and are very inconvenient because service users have to set up and manage by themselves. Thus, the present paper proposes a Semantic User Profiles Manager based on OSGi, middleware for the provision and extension of semantic services, in order to manage users' profiles dynamically regardless of service provider. In addition, this paper defines a personalized semantic profile that enables user profiling, ontological domain modeling and semantic reasoning. In order to test the validity of this paper, we implemented semantic profiles into a bundle running based on OSGi. When users enter the range of the service area and use various devices, the semantic service matches in correspondence with semantic user profiles. The proposed system can easily extend the matching of services to user profiles and matching between user profiles or between services.