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A dynamic user profiling technique in a AmI environment

Vitor Marques, Angelo Costa, Paulo Novais
2011 2011 World Congress on Information and Communication Technologies  
It is introduced a project that applies the Bayesian Networks and Case-Based Reasoning techniques to create and modulate user profiles in a coherent and dynamic way, using stochastic models and high-level  ...  Paramount with cognitive helping systems, that provide decisions and recommendations these actions can more accurate and user driven.  ...  Fig. 1 . 1 Modeling a profile intelligence, which are the Case-Based Reasoning and Bayesian Networks.  ... 
doi:10.1109/wict.2011.6141427 fatcat:t6gopvh7r5b5rhem6p7s44dy2i

Bayesian Model-based Personalized Recommendation Service

Jeong-Sig Kim, Eung-Sung Kim, Jin-Hong Kim
2017 International Journal of u- and e- Service, Science and Technology  
methods, user profiling information, query's pattern with Big Data of real world.  ...  This service is to allow user to customize the service itself, and proactively tailor services based on information from past service historical data.  ...  Bayesian Networks Bayesian networks are graphical models commonly used in probabilistic reasoning and artificial intelligence.  ... 
doi:10.14257/ijunesst.2017.10.7.06 fatcat:4mfgcqzxp5attntdo7onbm5vlu

Bayesian networks for victim identification on the basis of DNA profiles

C.J. Bruijning-van Dongen, K. Slooten, W. Burgers, W. Wiegerinck
2009 Forensic Science International: Genetics Supplement Series  
The ICIS project and the Ministry of Economic Affairs had no involvement in this research and resulting article. Conflict of interest None.  ...  For these reasons we have developed software for Bayesian network kinship analysis based on DNA profiles. The software is called Napoleon/Bonaparte.  ...  Matching can be direct (e.g. to match UIs with PEs (Personal Effects)) and indirect (UIs with MPs, using Bayesian networks). A list of LRs is presented to the user.  ... 
doi:10.1016/j.fsigss.2009.08.024 fatcat:bx6gl6wb5za5bbst3r7t5avwh4

A modular design of Bayesian networks using expert knowledge: Context-aware home service robot

Han-Saem Park, Sung-Bae Cho
2012 Expert systems with applications  
The proposed approach supplements uncertain sensor input using Bayesian network modeling and enhances the efficiency in modeling and reasoning processes using modular design based on domain knowledge.  ...  a number of Bayesian networks.  ...  Acknowledgements This research was supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and  ... 
doi:10.1016/j.eswa.2011.08.118 fatcat:dtqcaan2kffhfjgiddz46ajnkm

Bayesian Metanetworks for Modelling User Preferences in Mobile Environment [chapter]

Vagan Terziyan, Oleksandra Vitko
2003 Lecture Notes in Computer Science  
The foundation for the use of Bayesian networks and Markov models for user profiling in the information retrieval was given by Wong and Butz in [23] .  ...  A Bayesian network has proved to be a valuable tool for encoding, learning and reasoning about probabilistic (casual) relationships.  ...  As location of mobile user is being considered as a very important determinative attribute in modelling of user's decision making, the applications of Bayesian Metanetworks for mobile location-based systems  ... 
doi:10.1007/978-3-540-39451-8_27 fatcat:rwarcmdehjgd5hlljn4shbgjz4

Probabilistic Modeling for Context-Aware Service in Smart TV

Kyon-Mo Yang, Sung-Bae Cho
2013 2013 4th International Conference on Intelligent Systems, Modelling and Simulation  
To solve this problem, we propose context-aware service in the smart TV using modular Bayesian networks. Bayesian network can be designed by domain knowledge when there is not enough data.  ...  The smart TV contains a variety of functions causes a problem that the user has to learn the functions.  ...  ACKNOWLEDGMENT This research was supported by Korea Communications Commission(KCC) as a project, "Development of UX based Smart TV Environmental Status Recognition Technology"  ... 
doi:10.1109/isms.2013.64 fatcat:3ojslmqyfregpchfz736mwc7by

Stroke Prediction Context-Aware Health Care System

Hamid Mcheick, Hoda Nasser, Mohamed Dbouk, Ahmad Nasser
2016 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)  
This paper proposes a prediction framework based on ontology and Bayesian Belief Networks BBN to support a medical teams in every daily.  ...  and calculate the probability of high risk level for emergency cases.  ...  Then a Bayesian network, Based on the probabilistic model and our specific ontology, is derived with structure of Bayesian belief network.  ... 
doi:10.1109/chase.2016.49 dblp:conf/chase/McheickNDN16 fatcat:akfarbvxtbhjpoak3c7d5dntgy

A TV Program Recommender Framework

Na Chang, Mhd Irvan, Takao Terano
2013 Procedia Computer Science  
into television sets and set-top boxes.  ...  We give an overview of literature research about TV program recommender systems and propose a smart and social TV program recommender framework for Smart TV, which integrates the Internet and Web 2.0 features  ...  For example, learning from experience task could use content-based filtering methods such as Bayesian classifier, Case-based reasoning, and vector space model and so on.  ... 
doi:10.1016/j.procs.2013.09.136 fatcat:dj2jdwrsjzecjnba4a2zfcb26m

Health Recommender System Using Big Data Analytics

J.Archenaa, E.A.Mary Anita
2017 Zenodo  
Evidence-based medicine is a powerful tool to help minimize treatment variation and unexpected costs.  ...  Bayesian methods is becoming popular in medical research due its effectiveness in making better predictions.For example on training the model with the age of women and diabetes condition helps to predict  ...  Recommender systems outcomes are recommending diagnosis, health insurance, clinical pathway based treatment methods and alternative medicines to users based on their health profile similarity with others  ... 
doi:10.5281/zenodo.833884 fatcat:f536knjc3fb3fexzjrcgca47oe

Health Recommender System Using Big Data Analytics

J.Archenaa, E.A.Mary Anita
2017 Zenodo  
Evidence-based medicine is a powerful tool to help minimize treatment variation and unexpected costs.  ...  Bayesian methods is becoming popular in medical research due its effectiveness in making better predictions.For example on training the model with the age of women and diabetes condition helps to predict  ...  Recommender systems outcomes are recommending diagnosis, health insurance, clinical pathway based treatment methods and alternative medicines to users based on their health profile similarity with others  ... 
doi:10.5281/zenodo.833885 fatcat:olmkxvgv4nedpjp5t7j5owuybu

Detecting Credential Abuse in the Grid Using Bayesian Networks

Christopher Kunz, Nina Tahmasebi, Thomas Risse, Matthew Smith
2011 2011 IEEE/ACM 12th International Conference on Grid Computing  
Our approach combines modifications to the security infrastructure with a Bayesian classifier in order to provide a reliable method for detecting abusive Grid credential usage and alerting the legitimate  ...  user.  ...  Based on each VO's profile, we randomly generate user profiles and then generate credential usage accordingly.  ... 
doi:10.1109/grid.2011.23 dblp:conf/grid/KunzTRS11 fatcat:x2wjguun4fdlfhgywofm5pd7pi

Health Recommender System Using Big Data Analytics

J.Archenaa, E.A.Mary Anita
2017 Zenodo  
Evidence-based medicine is a powerful tool to help minimize treatment variation and unexpected costs.  ...  Bayesian methods is becoming popular in medical research due its effectiveness in making better predictions.For example on training the model with the age of women and diabetes condition helps to predict  ...  Recommender systems outcomes are recommending diagnosis, health insurance, clinical pathway based treatment methods and alternative medicines to users based on their health profile similarity with others  ... 
doi:10.5281/zenodo.834918 fatcat:gua3hpksmbckzogurxscykxwue

Finding Days-of-week Representation for Intelligent Machine Usage Profiling

Chiming Chang, Paul-Armand Verhaegen, Joost R. Duflou, Madalina M. Drugan, Ann Nowe
2013 Journal of Industrial and Intelligent Information  
We show how the probability models can be learned with Bayesian network classifiers and we highlight the importance of finding the optimal days-ofthe-week representation.  ...  In this paper, we discuss general aspects of generating usage profiles and propose a daily pattern based probability model for usage profiling.  ...  We propose a daily pattern based probability model for usage profiling and show how the model can be learned with Bayesian network classifiers.  ... 
doi:10.12720/jiii.1.3.148-154 fatcat:koumuazxgba7xghthnlb3jntiq

Bayesian Networks, Introduction and Practical Applications [chapter]

Wim Wiegerinck, Willem Burgers, Bert Kappen
2013 Intelligent Systems Reference Library  
The distinguishing feature in this application is that Bayesian networks are generated and computed on-the-fly, based on case information.  ...  In this chapter, we will discuss Bayesian networks, a currently widely accepted modeling class for reasoning with uncertainty.  ...  We thank Ender Akay, Kees Albers and Martijn Leisink (SNN), Mirano Spalburg (Shell E & P), Carla van Dongen, Klaas Slooten and Martin Slagter (NFI) for their collaboration.  ... 
doi:10.1007/978-3-642-36657-4_12 fatcat:2an3ado2vvczzjdh6hismrjume

Privacy preserving data mining for social networks

Brinal Colaco, Shamsuddin S. Khan
2014 2014 International Conference on Advances in Communication and Computing Technologies (ICACACT 2014)  
These hackers could either be third party agencies or individuals who are interested in knowing more about the users of the social networks.  ...  Advances in technology has made it possible for hackers and intruders to collect personal and professional data about individuals and the connections between them, such as their email correspondence and  ...  The results for different range of users are show in the tables below.A dataset with profile information of 2000 users was used for the experiments.  ... 
doi:10.1109/eic.2015.7230729 fatcat:wjwewd6opzbszmh6c3xdytfl3q
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