• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.17-24
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• 2007

Critical practicality problems are cause to search the presentation and contents according to user request and purpose in previous internet system. Recently, there are a lot of researches about dynamic adaptable ontology based system. We designed ontology based educational system which uses discrete probability and user profile. This system provided advanced usability of contents by ontology and dynamic adaptive model based on discrete probability distribution function and user profile in ontology educational systems. This models represents application domain to weighted direction graph of dynamic adaptive objects and modeling user actions using dynamically approach method structured on discrete probability function. Proposed probability analysis can use that presenting potential attribute to user actions that are tracing search actions of user in ontology structure. This approach methods can allocate dynamically appropriate profiles to user.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1570-1594
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• 2017

Social network services have recently changed from environments for simply building connections among users to open platforms for generating and sharing various forms of information. Existing user reputation computation methods are inadequate for determining the trust in users on social media where explicit ratings are rare, because they determine the trust in users based on user profile, explicit relations, and explicit ratings. To solve this limitation of previous research, we propose a user reputation computation method suitable for the social media environment by incorporating implicit as well as explicit ratings. Reliable user reputation is estimated by identifying malicious information raters, modifying explicit ratings, and applying them to user reputation scores. The proposed method incorporates implicit ratings into user reputation estimation by differentiating positive and negative implicit ratings. Moreover, the method generates user reputation scores for individual categories to determine a given user's expertise, and incorporates the number of users who participated in rating to determine a given user's influence. This allows reputation scores to be generated also for users who have received no explicit ratings, and, thereby, is more suitable for social media. In addition, based on the user reputation scores, malicious information providers can be identified.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.1-12
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• 2009

Today, Digital Right Management (DRM) is used to protect copyrights of digital contents from illegal reproduction and redistribution. Unfortunately, current DRM systems are causing user's discomfort because of lack of mutual compatibility. In order to overcome this drawback, technologies for interoperability of heterogeneous DRM systems are developing. In this paper, we study the protection profile for conversion technologies of heterogeneous DRM systems, using the Common Criteria. Especially, this paper is written by reuse of the existing protection profile. Therefore, performance analysis reveals that efficiency of time and cost is significantly improved. This protection profile can be used by contents provider and administrator who manage user's copyrights to reference data for copyright protection.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.19-25
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• 2019

We have developed a tool that uses finite element analysis (FEA) to rapidly evaluate a shaft-bearing system of machine tools. We extracted commercial data on suitable clamping units and defined the inner profile of the shaft to avoid needing direct user input to define the profile. We use a splitting algorithm to convert the shaft into beam elements with two diameters and length. To validate the tool, we used it to design and evaluate a shaft-bearing system and found that our tool automated the construction of an FE system model in a commercial FEA package as well as the static stiffness evaluation; both tasks were completed in seconds, demonstrating a significant reduction from the minutes normally required to complete these tasks manually.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.921-928
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• 2004

This paper proposed dynamic adaptive model based on discrete probability distribution function and user profile in web based HyperMedia educational systems. This modelsrepresents application domain to weighted direction graph of dynamic adaptive objects andmodeling user actions using dynamically approach method structured on discrete probability function. Proposed probabilitic analysis can use that presenting potential attribute to useractions that are tracing search actions of user in WebMedia structure. This approach methodscan allocate dynamically appropriate profiles to user.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1996.12a
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• pp.97-101
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• 1996

Municipal and sanitary landfills can pose environmental problems due to leachate, landfill gas md unstable geotechnical properties. Most governmental bodies delay the correction of landfill problems or landfill replacement until a crises stage is reached. The replacement of a landfill is often made difficult due to costly regulatory controls, public opposition to siting and the high cost of closure for the previous landfill unit. Solutions to extending landfill life and capacity Involve waste minimization by recycling, refuse compaction and waste-to-energy incineration. Incineration can reduce the volume of refuse by 50-95%. The largest installed bases of municipal waste Incinerators are located in Japan and the U.S. The volume of waste contained in a landfill can be estimated by load count tabulations, weight-and-volume measurements or a material balance analysis based on the trash profile of user categories. for an existing landfill, core samples may be collected and analyzed for use in a material balance analysis. Newly generated refuse contains approximately 50% of the heating value of coal. However, landfill properties vary significantly due to the waste profile of the contributors and biodegradation due to time and weathering. The volume of the Nanji-do landfill

• Journal of Ocean Engineering and Technology
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• v.23 no.1
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• pp.43-47
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• 2009

This paper compares theoretical wave profile and particle kinematics with experimental results generated by a 2 D wave tank. Particle velocity fields of compound waves were acquired using a PIV technique. Synchronization was applied to acquire images of the wave fields, and the time gap between these images was controlled by the user. This technique was applied to investigate the wave breaking mechanism, and the wave profile and velocity distribution in a wave breaking field was obtained.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.533-540
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• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.