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AutoBayesian: Developing Bayesian Networks Based on Text Mining [chapter]

Sandeep Raghuram, Yuni Xia, Jiaqi Ge, Mathew Palakal, Josette Jones, Dave Pecenka, Eric Tinsley, Jean Bandos, Jerry Geesaman
2011 Lecture Notes in Computer Science  
Bayesian network is a widely used tool for data analysis, modeling and decision support in various domains.  ...  In practice, Bayesian networks also need be updated when new data is observed, and literature mining is a very important source of new data after the initial network is constructed.  ...  A Sample Bayesian Network Derived from Text Derive Confidence Measure By using existing text mining techniques, causal associations can be extracted from geriatrics health care literature After the probabilities  ... 
doi:10.1007/978-3-642-20152-3_37 fatcat:wnj3vueftzdsromxpcbmqk34dm

Bridging Text Mining and Bayesian Networks

Sandeep Raghuram, Yuni Xia, Mathew Palakal, Josette Jones, Dave Pecenka, Eric Tinsley, Jean Bandos, Jerry Geesaman
2009 2009 International Conference on Network-Based Information Systems  
Bridging Text Mining and Bayesian Networks.  ...  Literature mining is a very important source of this new data after the initial network is constructed using the expert's knowledge.  ... 
doi:10.1109/nbis.2009.102 dblp:conf/nbis/RaghuramXPJPTBG09 fatcat:w5mmhiyr3rbtzd2ljgjqomvwmy

Physical Fitness Evaluation of College Students at the Stage of Physical Exercise Behavior Based on Bayesian and Data Mining

Lei Wang, Mei Yang, Tongguang Ni
2022 Scientific Programming  
evaluation index system was realized through Bayesian network topology to realize the physical fitness evaluation in the physical exercise behavior stage.  ...  Therefore, this study proposed a physical fitness evaluation method in the stage of physical exercise behavior based on Bayesian and data mining for the college students.  ...  Based on the Bayesian network topology, the key risk factors and key risk relationships in the social network were analyzed, and the middle centrality of points was used for physical fitness evaluation  ... 
doi:10.1155/2022/9582690 fatcat:z2p5y52pjbfvzdrfk67c574npq

Constraint-Based Querying for Bayesian Network Exploration [chapter]

Behrouz Babaki, Tias Guns, Siegfried Nijssen, Luc De Raedt
2015 Lecture Notes in Computer Science  
This CP4BN framework employs a rich set of constraints and is able to emulate a range of existing queries from both the Bayesian network and the constraint-based data mining literature.  ...  Understanding the knowledge that resides in a Bayesian network can be hard, certainly when a large network is to be used for the first time, or when the network is complex or has just been updated.  ...  We gratefully acknowledge useful comments and contributions from Guy Van den Broeck and Angelika Kimmig.  ... 
doi:10.1007/978-3-319-24465-5_2 fatcat:fywf7tp5hvhgtdqpfltyjih62m

Understanding Behavioral Intention to Participate in Virtual Communities

Hsiu-Fen Lin
2006 CyberPsychology & Behavior  
A Bayesian network represents probability distributions [23, 24] .  ...  Jrip, part, oner method, Multilayer Perceptron (Neural Networks), and Bayesian Networks have been chosen as the data mining techniques in order to examine desire and intention to participate in virtual  ... 
doi:10.1089/cpb.2006.9.540 pmid:17034320 fatcat:qwcvq2wa7reitlljtzqejfo2ye

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

Anuj Sharma, Prabin Kumar Panigrahi
2012 International Journal of Computer Applications  
The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions  ...  This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques  ...  CONCLUSION AND FUTURE RESEARCH This paper reviewed the literature describing use of data mining algorithms including statistical test, regression analysis, Neural Network, decision tree, Bayesian network  ... 
doi:10.5120/4787-7016 fatcat:ifmqadjmwfeufi57cizszqhgzy

Model to Predict the Behavior of Customers Churn at the Industry

Keyvan VahidyRodpysh
2012 International Journal of Computer Applications  
In order to check the model presented with a desire to review a decision tree classification methods (C5.0, CART, CHAID, and Quest), Bayesian networks and neural networks will be paid with respect to sample  ...  In the present study are to go through a database collected from 300 customers, including an insurance company in Iran has been used.  ...  [1] As seen in Table 1 , modeling techniques to predict the frequency churn customers using data mining these include methods such as decision trees, logistic regression, neural networks, Bayesian  ... 
doi:10.5120/7702-1059 fatcat:4424i4whmfdcbdo46vpqgjamfy

Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data

Jinlian Wang, Yiming Zuo, Yan-gao Man, Itzhak Avital, Alexander Stojadinovic, Meng Liu, Xiaowei Yang, Rency S. Varghese, Mahlet G Tadesse, Habtom W Ressom
2015 Journal of Cancer  
To address these challenges, a number of pathway and network based approaches have been introduced.  ...  This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.  ...  versatile in network applications, such as network importing, network integrating, inference customization, literature mining, topological clustering, functional enrichment, network comparison, and programmatic  ... 
doi:10.7150/jca.10631 pmid:25553089 pmcid:PMC4278915 fatcat:7ngrvqd2ijbixoxdhx5xusdyoq

A Survey on Rice Crop Yield Prediction in India Using Improved Classification Technique

Kolin Sukhadia, M. B. Chaudhari
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
To achieve more significant result, To increase classification accuracy and reducing classification errors, our research uses classification method Bayesnet based adaboost will be proposed in work.  ...  This study[28] examine Modeling Rainfall Prediction Using Data Mining Method: A Bayesian Approach data mining method for modeling rainfall prediction.  ...  This study [21] examine Bayesian Network Classifiers in Weka.  ... 
doi:10.32628/cseit1951122 fatcat:x2vj3pnoxbgtldittqadudsrme

Bayesian Networks to Predict Data Mining Algorithm Behavior in Ubiquitous Computing Environments [chapter]

Aysegul Cayci, Santiago Eibe, Ernestina Menasalvas, Yucel Saygin
2011 Lecture Notes in Computer Science  
Thus, in this paper, Bayesian networks are used to extract the effects of data mining algorithm parameters on the final model obtained, both in terms of efficiency and efficacy in a given situation.  ...  The growing demand of data mining services for ubiquitous environments motivates deployment of data mining algorithms that use context to adapt their behavior to present circumstances.  ...  Comparison of Results We propose to use Bayesian network for automatizing the parameter tuning of data mining algorithms.  ... 
doi:10.1007/978-3-642-23599-3_7 fatcat:3avuwk3scnb73icrq5pqdxogri

Data Mining in the Molecular Biology Era — A Study Directed to Carbohydrates Biosynthesis and Accumulation in Plants [chapter]

Renato Vicentini, Marcelo Menossi
2009 Data Mining and Knowledge Discovery in Real Life Applications  
To simulate our model we mined literature and databases for kinetic data using the SABIO-RK and Kinetikon databases.  ...  With the identified coexpressed genes, we constructed a Bayesian networks by using the BNArray tool (Table 1) .  ...  We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.  ... 
doi:10.5772/6456 fatcat:72r6gtyfhjacbbaootuzl2bzee

An Experiment on Using Bayesian Networks for Process Mining [article]

Catarina Moreira
2015 arXiv   pre-print
In this sense, this work proposes a new approach to perform process mining using Bayesian Networks.  ...  Experiments made over a Loan Application Case study suggest that Bayesian Networks are adequate structures for process mining and enable a deep analysis of the business process model that can be used to  ...  However, Markov Chains and Petri Nets are the models that are most used in the literature of process mining (Tiwari et al. 2008) .  ... 
arXiv:1503.07341v1 fatcat:kxtwuhrlrzhzfanmzdfo2w5r6a

Probabilistic Measures for Interestingness of Deviations - A Survey

Adnan Masood, Sofiane Ouaguenouni
2013 International Journal of Artificial Intelligence & Applications  
In this brief survey, we review the current state of literature around interestingness of deviations, i.e. outliers with specific interest around probabilistic measures using Bayesian belief networks.  ...  Association rule mining has long being plagued with the problem of finding meaningful, actionable knowledge from the large set of rules.  ...  This framework idea was further formalized by [39] in "Using a Bayesian Network as Background Knowledge" and later matured in ""Scalable pattern mining with Bayesian networks as background knowledge"  ... 
doi:10.5121/ijaia.2013.4201 fatcat:3bwuzx3egbc7xk62g3zosizrcu

Predictive data mining approaches in medical diagnosis: A review of some diseases prediction

Ramin Ghorbani, Rouzbeh Ghousi
2019 International Journal of Data and Network Science  
The study attempts to determine the most efficient data mining methods used for medical diagnosing purposes.  ...  Data mining is the process of determining and analyzing hidden information from different perspectives to obtain useful knowledge.  ...  This paper studied different methods including DT, Bayesian Network, Logistic Regression, SVM, Naive Bayes, Association Rule Mining, and Artificial Neural Network.  ... 
doi:10.5267/j.ijdns.2019.1.003 fatcat:tzavawufrfcy3djjeo2dve63fm

Page 1123 of Pharmacotherapy Vol. 24, Issue 9 [page]

2004 Pharmacotherapy  
Wellesley Hills, MA),”° and a neural network-based Bayesian method know as the Bayesian Confidence Propagation Neural Network (BCPNN).’  ...  APPLICATION OF AN EMPIRIC BAYESIAN DATA MINING ALGORITHM.  ... 
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