• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.160-166
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a user preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or ron-spam in a meaningful way. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.

• Convergence Security Journal
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• v.19 no.2
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• pp.73-81
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• 2019

In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.

• Journal of Technology Innovation
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• v.23 no.1
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• pp.1-36
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• 2015

The purpose of this research is to find individual user's preference for cloud storage service such as Daum Cloud, Naver N-Drive, GoogleDrive, Dropbox, SkyDrive and iCloud. Through literature reviewed and pilot tests, 6 attributes of cloud storage service (storage capacity, perceived cost, collaboration, accessibility, social influence and perceived security) were selected and all 6 attributes had significant effects on the preference of cloud storage service by conjoint analysis. The results shows that the user's willingness to pay is estimated 10,553 won for the free storage, 4,646 won for the function for mobile accessibility, and 2,443 won for more reliable cloud computing service provider. This study has significance to apply conjoint analysis with economic, technological, and environmental factors to cloud storage service (SaaS) and shed light on policy promotion of next generation of cloud computing ecosystem by user perception with willingness to pay on the storage service.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.805-812
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• 2005

Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.863-870
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• 2002

The current class scheduling has difficulties in reflecting students' preferences for the classes that they want to take and forecasting the demands of classes. Also, it is usually a repetitive and tedious work to allocate classes to limited time and cesourres Although many research studios in task allocation and meeting scheduling intend to solve similar problems, they have limitations to be directly applied to the class-scheduling problem. In this paper. a class scheduling system using multi agents-based negotiation is suggested. This system consists of student agents, professor agents and negotiation agents each agent arts in accordance with its respective human user's preference and performs the repetitive and tedious process instead of the user The suggested system utilizes negotiation cost concept to derive coalition in the agent's negotiation. The negotiation cost is derived from users' bidding prices on classes, where each biding price represents a user's preference on a selected class. The experiments were performed to verify the negotiation model in the scheduling system. The result of the experiment showed that it could produce a feasible scheduling solution minimizing the negotiation cost and reflecting the users' performance. The performance of the experiments was evaluated by a class success ratio.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.12-21
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• 2010

In this paper, we suggest Location Recognition System using Sensor Network; it distinguishes locations. Furthermore, this paper proposes Intelligent Navigation System which presents the proper route for the user. INS evaluates the user's preference, tendency and environmental state using Sensor Network Module and current driving information. This system also uses Soft-computing method to learn and infer the person’s preference and tendency. This paper defines Intelligent Assistance Module (IAM) which is a connector in between a user and a robot; it is portable. All in all, we created a basic intelligent robot, Location Recognition System, and Environment Sensor Modules; we verified the proposed algorithm through computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5344-5356
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• 2018

Nowadays with the help of Location-Based Social Networks (LBSNs), users of Point-of-Interest (POI) recommendation service in LBSNs are able to publish their geo-tagged information and physical locations in the form of sign-ups and share their experiences with friends on POI, which can help users to explore new areas and discover new points-of-interest, and promote advertisers to push mobile ads to target users. POI recommendation service in LBSNs is attracting more and more attention from all over the world. Due to the sparsity of users' activity history data set and the aggregation characteristics of sign-in area, conventional recommendation algorithms usually suffer from low accuracy. To address this problem, this paper proposes a new recommendation algorithm based on a novel Preference-Content-Region Model (PCRM). In this new algorithm, three kinds of information, that is, user's preferences, content of the Point-of-Interest and region of the user's activity are considered, helping users obtain ideal recommendation service everywhere. We demonstrate that our algorithm is more effective than existing algorithms through extensive experiments based on an open Eventbrite data set.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.1-12
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• 2004

In recent years, with the advent of e-Commerce the need for personalized services and one-to-one marketing has been emphasized. To be successful in increasingly competitive Internet marketplace, it is essential to capture customer loyalty. In this paper, we provide an intelligent agent approach to incorporate human sensibility into an one-to-one recommendation service in cyber shopping mall. Our system exploits human sensibility ergonomics and on-line preference matching technologies to tailor to the customer the suggestion of goods and the description of store catalog. Customizing the system`s behavior requires the parallel execution of several tasks during the interaction （e. g., identifying the customer`s emotional preference and dynamically generating the pages of the store catalog）. The recommendation agent system composed of five modules including specialized agents carries on these tasks. By presenting goods that are consistent with user interests as well as user sensibility, the accuracy and satisfaction of the recommendation service may be improved.

• Proceedings of the Safety Management and Science Conference
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• 2011.11a
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• pp.695-716
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• 2011

In the future, smartphone convergences are not only based on the on/offline integration, but also with the integration between mobile communications and broadcasts. Therefore, there is a need to search for new direction of mobile device that enables variety user applications that are different from the existing size and application issue. The aim of this reserch is to improve user interface of smartphone's functional attribute. The survey results in this paper showed that the most preferable attribute of smartphone among the 8 was the wireless internet 25.3%, followed by messaging 20% and application 19.8%, which totaled to 62.5%. But the samples used were mostly limited to those aged 20 through 30. So the results are not considered as a representative preference of all smartphone users, and should be considered otherwise before materializing them to a product. Therefore, for the more liable results the further research should be conducted to gather data from a variety of users of all ages, and the functional attribute should be analysed through QFD.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.53-63
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• 2002

As the microelectronics technology is developed, new types d smart intelligent produce are being emerged. OSD user interface is one of the critical factor in this kind of product, especially brown goods and information devices, as it is responsible for input and output function. OSD is being treated as accompaniment to hardware in spite of its importance, and therefore is developed from only simple and separate usability testing based on performance measurement. This study propose a usability evaluation method of OSD based on subjective preference to support existing usability testing. The purpose of this analysis is to make dear what is important factor and how its preference level is from the user's viewpoint. The various attributes of OSD are clarified from user's questionaire and interview, and orthogonal array is generated with specifed factor levels. The prototypes are generated from rapid prototyping tool and tested in natural simulation environment. The preference data which collected in this usability testing is analyzed with conjoint analysis module. This usability evaluation is not the final stage in user interface design process but the early famed and circulated stage.