A Comparative Study on Latest Substring Association Rule Mining and Hidden Markov Model

2017 International Conference on Computer, Electrical & Communication Engineering (ICCECE) ◽

10.1109/iccece.2017.8526213 ◽

2017 ◽

Author(s):

Rudra Prasad Chatterjee ◽

Chhanda Ray ◽

Rajib Bag

Keyword(s):

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

Association Rule ◽

Association Rule Mining ◽

Hidden Markov ◽

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Integration of profile hidden Markov model output into association rule mining

Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05 ◽

10.1145/1081870.1081933 ◽

2005 ◽

Author(s):

Christopher Besemann ◽

Anne Denton

Keyword(s):

Markov Model ◽

Hidden Markov Model ◽

Association Rule ◽

Association Rule Mining ◽

Hidden Markov ◽

Model Output ◽

Rule Mining ◽

Profile Hidden Markov Model

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A comparative study of a hidden Markov model detector for atrial fibrillation

Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468) ◽

10.1109/nnsp.1999.788166 ◽

2003 ◽

Author(s):

B. Young ◽

D. Brodnick ◽

R. Spaulding

Keyword(s):

Atrial Fibrillation ◽

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

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A Comparative Study on the Performance of Hidden Markov Model in Appliance Modeling

10.1109/icpee54380.2021.9662546 ◽

2021 ◽

Author(s):

Hebatullah M. Malik ◽

Nema Salem ◽

Maha S. AlSabban

Keyword(s):

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

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Comparative Study of Association Rule Mining and MiSTIC in Extracting Spatio-temporal Disease Occurrences Patterns

2012 IEEE 12th International Conference on Data Mining Workshops ◽

10.1109/icdmw.2012.131 ◽

2012 ◽

Author(s):

Vipul Raheja ◽

K.S. Rajan

Keyword(s):

Comparative Study ◽

Association Rule ◽

Association Rule Mining ◽

Rule Mining ◽

Spatio Temporal

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Comparative Study of Techniques to Improve Efficiency of Association Rule Mining

Procedia Computer Science ◽

10.1016/j.procs.2015.04.233 ◽

2015 ◽

Vol 49 ◽

pp. 104-110 ◽

Author(s):

Meera Narvekar ◽

Apurva Kulkarni ◽

S.S. Santha

Keyword(s):

Comparative Study ◽

Association Rule ◽

Association Rule Mining ◽

Rule Mining ◽

Improve Efficiency

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Activity Recognition in Surfing - A Comparative Study between Hidden Markov Model and Support Vector Machine

Procedia Engineering ◽

10.1016/j.proeng.2016.06.279 ◽

2016 ◽

Vol 147 ◽

pp. 912-917 ◽

Author(s):

Hannes Hoettinger ◽

Franziska Mally ◽

Anton Sabo

Keyword(s):

Support Vector Machine ◽

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

Activity Recognition ◽

Hidden Markov ◽

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A comparative study of hidden Markov model and conditional random fields on a Yorùba part-of-speech tagging task

2017 International Conference on Computing Networking and Informatics (ICCNI) ◽

10.1109/iccni.2017.8123784 ◽

2017 ◽

Author(s):

Ikechukwu I. Ayogu ◽

Adebayo O. Adetunmbi ◽

Bolanle A. Ojokoh ◽

Samuel A. Oluwadare

Keyword(s):

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

Random Fields ◽

Conditional Random Fields ◽

Hidden Markov ◽

Part Of Speech Tagging ◽

Part Of Speech ◽

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Comparative Study on Hidden Markov Model Versus Support Vector Machine: A Component-Based Method for Better Face Recognition

2013 UKSim 15th International Conference on Computer Modelling and Simulation ◽

10.1109/uksim.2013.44 ◽

2013 ◽

Author(s):

M. Srinivasan ◽

S. Raghu

Keyword(s):

Support Vector Machine ◽

Face Recognition ◽

Comparative Study ◽

Markov Model ◽

Hidden Markov Model ◽

Hidden Markov ◽

Support Vector ◽

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A comparative study for landslide susceptibility mapping using GIS-based multi-criteria decision analysis (MCDA), logistic regression (LR) and association rule mining (ARM)

Engineering Geology ◽

10.1016/j.enggeo.2015.09.007 ◽

2016 ◽

Vol 203 ◽

pp. 45-55 ◽

Author(s):

Arzu Erener ◽

Alev Mutlu ◽

H. Sebnem Düzgün

Keyword(s):

Logistic Regression ◽

Comparative Study ◽

Decision Analysis ◽

Association Rule ◽

Landslide Susceptibility ◽

Association Rule Mining ◽

Susceptibility Mapping ◽

Landslide Susceptibility Mapping ◽

Rule Mining ◽

Multi Criteria Decision Analysis

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A comparative study of discretization approaches for granular association rule mining

2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) ◽

10.1109/ccece.2013.6567823 ◽

2013 ◽

Author(s):

Xu He ◽

Fan Min ◽

William Zhu

Keyword(s):

Comparative Study ◽

Association Rule ◽

Association Rule Mining ◽

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