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Recommending mobile content using content diffusion and user preference transition

Recommending mobile content using content diffusion and user...

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2008 International Conference on e-Learning, e-Business, Enterprise information Systems, and e-Government, EEE 2008

作者： Lee, Tong Queue Lee, Eunchang Park, Young Park, Yongtae Department of Mobile Internet Dongyang Technical College Seoul Korea Republic of Graduate Program in Technology and Management Seoul National University Seoul Korea Republic of Department of Computer Science and Information Systems Bradley University Peoria IL United States Department of Industrial Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)1601320639

Recommendation accuracy is especially important in mobile e-commerce environments due to the limited screen size of mobile devices and relatively expensive connection costs. Mobile content tends to be fashionable and are geared for young users. This paper presents a novel method of building a more accurate recommender system for mobile content in a mobile ecommerce environment. The method is based on collaborative filtering, and models content diffusion and user preference transition and incorporates them in constructing pseudo ratings from implicit feedback data. In a variety of experiments, recommender systems based on the method showed significantly better recommendation accuracy than a pure collaborative filtering-based recommender system.

关键词： Collaborative filtering

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Comparisons of classifier algorithms: Bayesian network, C4.5, decision forest and NBTree for Course Registration Planning model of undergraduate students

Comparisons of classifier algorithms: Bayesian network, C4.5...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Pathom Pumpuang Anongnart Srivihok Prasong Praneetpolgrang Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand Master of Science Program in Information Technology Graduate School Sripatum University Bangkok Thailand

The success rate of computer science and engineering students in private universities are not high. It is helpful to find the model to assist students in registration planning. The objective of this research is to propose the classifier algorithm for building course registration planning model (CRPM) from historical dataset. The algorithm is selected by comparing performances of four classifiers include Bayesian network, C4.5, Decision Forest and NBTree. The dataset were obtained from student enrollments including grade point average (GPA) and grades of undergraduate students whose majors were computer science or computer engineering. These dataset included grades in each subject of first and second year students from a private university in Thailand. Results showed that NBTree seemed to be the best of four classifiers which had highest prediction power. NBTree was used to generate CRP model which can be used to predict student class of GPA and consider student course sequences for registration planning.

关键词： Bayesian methods computer science Predictive models Data mining Decision trees Noise cancellation information technology Data analysis computer science education Path planning

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A Security Coordination Model for an Inter-Organizational information Incidents Response Supporting Forensic Process

A Security Coordination Model for an Inter-Organizational In...

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International Conference on Networked Computing and Advanced information Management (NCM)

作者： Kimoon Jeong Junhyung Park Minsoo Kim Bongnam Noh Interdisciplinary Program of Information Security Chonnam National University South Korea Division of Electronics Computer & Information Engineering Chonnam National University South Korea Korea Institute of Science and Technology Information South Korea Department of Information Security Mokpo National University South Korea

The high cost for information security incident response makes organizations hesitate to possess their own expert security team. Also organizations are still reluctant to share their own security circumstances with external organizations. By the way, they hope experts will help to defend against cyber threats without losing their reputations. To satisfy these requests of organizations, we propose a security coordination model that supports security incidents response in an organizational architecture, in this paper. Besides, our model has cyber forensic functions for collecting digital evidences from real time monitoring and on-site investigation of the incidents and reporting the analysis results to authorized organizations effectively.

关键词： Security Organizations Monitoring Real time systems information security computer architecture Law enforcement

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Using Bayesian Network for planning course registration model for undergraduate students

Using Bayesian Network for planning course registration mode...

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Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST

作者： Pathom Pumpuang Anongnart Srivihok Prasong Praneetpolgrang Somchai Numprasertchai Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand Master of Science Program in Information Technology Graduate School Sripatum University Bangkok Thailand Department of Computer Engineering Faculty of Engineer Kasetsart University Bangkok Thailand

ISBN: (纸本)9781424414895

The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registered by undergraduate students whose majors are computer science or engineering. The data set was obtained from student enrollments and include GPA and grades in each subject for first and second year students from a private university in Thailand. Evaluations show that the predictive power of this model is acceptable. The implications from this studypsilas findings suggest that the model can be applied for advising students in planning courses to be registered in each semester. Further, the model appears to be useful for improving curriculum development in order to fit both studentspsila and university requirements.

关键词： Bayesian methods Biological system modeling computers Education Computational modeling Brain modeling Brain models

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A decision support system for evaluating international student applications

A decision support system for evaluating international stude...

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37th Annual Frontiers in EducationConference

作者： Hien, Nguyen Thi Ngoc Haddawy, Peter Computer Science and Information Management Program Asian Institute of Technology

ISBN: (纸本)9781424410835

In today's transnational admission environment, evaluating applicant qualifications is becoming increasingly challenging. While standardized tests can be helpful, studies have shown that they are rather noisy predictors of performance. Predicting educational outcome is a viable alternative in such heterogeneous environments. Performance prediction models can be built by applying data mining techniques to enrollment data. In this paper we present an approach to using Bayesian networks to predict graduating cumulative Grade Point Average based on applicant background at the time of admission. While such prediction models can be helpful, their recommendations may not be followed by departmental faculty members making admission decisions if they are presented as black boxes. We thus present a novel approach to deriving a case-based retrieval mechanism from the Bayesian network prediction model in such a way that the similarity measure used by the case-based system is consistent with the predictive model. The case-based component retrieves the past student most similar to the applicant being evaluated. The Bayesian network model is evaluated using stratified ten-fold cross validation.

关键词： Bayesian networks case-based retrieval student evaluation

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Flagellar swimming for medical micro robots: Theory, experiments and application

Flagellar swimming for medical micro robots: Theory, experim...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Gabor Kosa Peter Jakab Nobuhiko Hata Ferenc Jolesz Zipi Neubach Moshe Shoham Menashe Zaaroor Gabor Szekely Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland Harvard Medical School Boston MA USA Division of MRI and Image Guided Therapy Program at Department of Radiology Brigham and Women's Hospital Boston MA USA Faculty of Mechanical Engineering Technion-Israel Institute of Technology Haifa Israel Department of Neurosurgery Rambam Medical Center Haifa Israel

Flagellar swimming is one of the swimming methods used by micro-organisms to advance in aquatic environment. The undulating motion of the flagella was successfully imitated to create propulsion for a medical swimming micro robot. The influence of a head section on the performance of such a robot is shown analytically. Swimming experiments demonstrate forward and backward swimming of a novel magnetically driven swimming tail. We intend to use the flagellar swimming tail in a three tail configuration for neurosurgical intervention in the ventricular system.

关键词： Medical robotics Tail Medical diagnostic imaging Propulsion Magnetosphere Neurosurgery Intestines computer vision Laboratories information technology

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Deriving financial aid optimization models from admissions data

Deriving financial aid optimization models from admissions d...

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37th ASEE/IEEE Frontiers in Education Conference, FIE

作者： Van Thanh, Le Haddawy, Peter Asian Institute of Technology Computer Science and Information Management Program

ISBN: (纸本)1424410843

This paper presents a novel approach to deriving probabilistic models that predict enrollment given applicant background and the amount of financial aid offered. Our Bayesian network models can be used to optimize various enrollment objectives. We present a novel efficient optimization algorithm that uses the models to maximize expected tuition revenue under capacity constraints including student-faculty ratio and accommodation. We demonstrate and evaluate our approach using four years of graduate admissions data from the Asian Institute of technology, consisting of 7,788 applicants from 84 different countries. This data set is particularly challenging since reliable family income data is not available for students from most of these countries. Evaluating the Bayesian network model with 10-fold cross validation yields an ROC Az value of 0.8451, with a predictive accuracy of 82.70% at a threshold of 0.5. Comparing the results of the tuition revenue optimization model to the institute's current financial aid allocation practice shows that if single-term tuition revenue is the sole optimization criterion, the institute can achieve its current enrollment numbers while realizing significant savings in its financial aid budget. The prediction and optimization software is currently being incorporated into the institute's online admissions processing system. ©2007 IEEE.

关键词： Bayesian networks

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A comparative analysis of techniques for predicting academic performance

A comparative analysis of techniques for predicting academic...

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37th Annual Frontiers in EducationConference

作者： Nghe, Nguyen Thai Janecek, Paul Haddawy, Peter Computer Science and Information Management Program Asian Institute of Technology (AIT) 12120 Thailand AIT Thailand Can Tho University Viet Nam

ISBN: (纸本)9781424410835

This paper compares the accuracy of Decision Tree and Bayesian Network algorithms for predicting the academic performance of undergraduate and postgraduate students at two very different academic institutes: Can Tho University (CTU), a large national university in Viet Nam;and the Asian Institute of technology (AIT), a small international postgraduate institute in Thailand that draws students from 86 different countries. Although the diversity of these two student populations is very different, the data-mining tools were able to achieve similar levels of accuracy for predicting student performance: 73/71% for {fail, fair, good, very good} and 94/93% for {fail, pass} at the CTU/AIT respectively. These predictions are most useful for identifying and assisting failing students at CTU (64% accurate), and for selecting Very Good students for scholarships at the AIT (82% accurate). In this analysis, the Decision Tree was consistently 3-12% more accurate than the Bayesian Network. The results of these case studies give insight into techniques for accurately predicting student performance, compare the accuracy of data mining algorithms, and demonstrate the maturity of open source tools.

关键词： Bayesian Networks data mining Decision Trees prediction

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Overcoming Bandwidth and Satellite Communications Limitations to Accelerate Applications of Remote Sensing and High Performance Computing for Sustainable African Development: Contributions from Egypt, Nigeria and South Africa

Overcoming Bandwidth and Satellite Communications Limitation...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gilbert L. Rochon Magdy Wahab Gamal El Afandi Ado Dan-Isa Happy Sithole Khomotso Kganyago Souleymane Fall Joseph Quansah Akilah Martin Bereket Araya Chetan Maringanti Cliff Robinson Kaiem L. Frink Jean Pierre Antelo Rosen Center for Advanced Computing Purdue Terrestrial Observatory Purdue University-Information Technology IN USA Department of Astronomy & Meteorology Faculty of Science Cairo University Cairo Egypt Department of Meteorology & Astronomy Al-Azhar University Cairo Egypt Department of Computer Engineering Bayero University Kano Nigeria Center for High Performance Computing CHCP-CSIRO Cape Town South Africa Department of Agricultural & Biological Engineering Purdue University West Lafayette IN USA School for New Learning De Paul University Chicago IL USA Purdue Research Opportunities Program West Lafayette IN USA

Sixty-two years after the first photos of earth taken by a camera aboard a V-2 rocket in October, 1946, and forty-eight years since the first CORONA satellite images were captured, the status of remote sensing research and applications within the African continent has made dramatic progress. Many African countries now have remote sensing research centers, within government agencies, research institutes and universities. Some countries in Africa currently have earth observing and/or telecommunications satellites in orbit and/or have such assets in various planning stages. The authors document such progress, in addition to the constraints to further applications of remote sensing for sustainable development in Africa, with special reference to data distribution constraints. Moreover, the authors address the urgency for bandwidth improvements within the African continent, so as to enable sustainable development initiatives to benefit from advances in high performance computing, required for ab initio near-real-time analysis of satellite-data. Such capabilities, it is argued, are propaedeutic for time-critical initiatives, such as vulnerability assessment, disaster preparedness and mitigation, emergency response, humanitarian assistance and post-calamity reconstruction, associated with a wide array of biogenic and anthropogenic disasters. Case studies of advances in infrastructure for satellite remote sensing and high performance computing, with implications for sustainable development in Africa, are provided from Egypt, Nigeria and South Africa.

关键词： Bandwidth Satellite communication Acceleration Remote sensing High performance computing Africa Sustainable development Earth Continents Cameras

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Perceptual-based region extraction from hand drawn sketches

Perceptual-based region extraction from hand drawn sketches

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3rd IASTED International Conference on Advances in computer Science and technology, ACST 2007

作者： Waranusast, Rattapoom Computer Science and Information Management Program Asian Institute of Technology P.O. Box 4 Khlong Luang Pathumthani 12120 Thailand

ISBN: (纸本)9780889866560

Pen-based computing devices have become more popular and more important, because it facilitates a natural way of input to users. To develop pen-based systems, automatic interpretation of sketches is crucial. However, this task is sensitive to drawing styles. This paper proposes a stroke grouping method based on Gestalt theory. The proposed algorithm group strokes into regions, each stroke is split into smaller stroke segments according to its corners and junctions. Then, for every stroke segments that can form closed loops, all possible regions are searched. Applying the notion of law of continuity in Gestalt theory to a set of all possible regions, scores of good continuity and convexity of all regions can be computed. The region with the best score is stored and extracted from the sketch. This iterative process is repeated until no stroke segments are left in the set of closed-loop segments. The algorithm implemented and tested on a tablet PC showed good results.

关键词： Iterative methods

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