Combining Correlation-Based Feature and Machine Learning for Sensory Evaluation of Saigon Beer

[1]  Van-Nam Huynh,et al.  A Novel Hybridization of ARIMA, ANN, and K-Means for Time Series Forecasting , 2017, Int. J. Knowl. Syst. Sci..

[2]  Van-Nam Huynh,et al.  Estimating the Optimal Number of Clusters in Categorical Data Clustering by Silhouette Coefficient , 2019, Communications in Computer and Information Science.

[3]  Branko Balla,et al.  Classification of Slovak white wines using artificial neural networks and discriminant techniques , 2009 .

[4]  J. Platt.  Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[5]  Shouyang Wang,et al.  A New Back-Propagation Neural Network Algorithm for a Big Data Environment Based on Punishing Characterized Active Learning Strategy , 2013, Int. J. Knowl. Syst. Sci..

[6]  José Pedro Santos,et al.  Enrichment sampling methods for wine discrimination with gas sensors , 2008 .

[7]  Sirli Seisonen,et al.  The current practice in the application of chemometrics for correlation of sensory and gas chromatographic data. , 2016, Food chemistry.

[8]  Sinan Çalik,et al.  A New Approach Using Hidden Markov Model and Bayesian Method for Estimate of Word Types in Text Mining , 2017, Int. J. Knowl. Syst. Sci..

[9]  Van-Nam Huynh,et al.  A method for k-means-like clustering of categorical data , 2019, Journal of Ambient Intelligence and Humanized Computing.

[10]  Hari Niwas Mishra,et al.  Fuzzy logic (similarity analysis) approach for sensory evaluation of chhana podo , 2013 .

[11]  Van-Nam Huynh,et al.  k-PbC: an improved cluster center initialization for categorical data clustering , 2020, Applied Intelligence.

[12]  Van-Nam Huynh,et al.  An efficient algorithm for mining periodic high-utility sequential patterns , 2018, Applied Intelligence.

[13]  Shouyang Wang,et al.  A Hybrid Forecasting Model for Non-Stationary Time Series: An Application to Container Throughput Prediction , 2012, Int. J. Knowl. Syst. Sci..

[14]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[15]  Van-Nam Huynh,et al.  Developing Evaluation Criteria for Partner Selection in Tourism Supply Chain Networks , 2017, Int. J. Knowl. Syst. Sci..

[16]  Li Yanxiao,et al.  Rapid detecting total acid content and classifying different types of vinegar based on near infrared spectroscopy and least-squares support vector machine. , 2013, Food chemistry.

[17]  Jing Liu,et al.  Instrumental and sensory characterisation of Solaris white wines in Denmark. , 2015, Food chemistry.

[18]  Manoj Khandelwal,et al.  Evaluation and prediction of blast induced ground vibration using support vector machine , 2010 .

[19]  Y. Sagara,et al.  Gas chromatography/olfactometry and electronic nose analyses of retronasal aroma of espresso and correlation with sensory evaluation by an artificial neural network. , 2010, Journal of food science.

[20]  Daniel Granato,et al.  Chemical Composition, Sensory Properties, Provenance, and Bioactivity of Fruit Juices as Assessed by Chemometrics: A Critical Review and Guideline. , 2014, Comprehensive reviews in food science and food safety.

[21]  Cheng Zhong,et al.  Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods. , 2014, Food chemistry.

[22]  Van-Nam Huynh,et al.  Grading Sewing Operator Skill Using Principal Component Analysis and Ordinal Logistic Regression , 2018, Int. J. Knowl. Syst. Sci..

[23]  Tom Rodden,et al.  A Consumer-Centric Open Innovation Framework for Food and Packaging Manufacturing , 2015, Int. J. Knowl. Syst. Sci..

[24]  Phuc Do,et al.  Social Network Analysis Based on Topic Model with Temporal Factor , 2018, Int. J. Knowl. Syst. Sci..

[25]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[26]  J. Albert Mayan,et al.  Anomaly Detection by Using CFS Subset and Neural Network with WEKA Tools , 2019 .

[27]  Herbert Stone,et al.  The role of sensory evaluation in the food industry , 1993 .

[28]  Jana Hajslova,et al.  Recognition of beer brand based on multivariate analysis of volatile fingerprint. , 2010, Journal of chromatography. A.

[29]  R. Poppi,et al.  Least-squares support vector machines and near infrared spectroscopy for quantification of common adulterants in powdered milk. , 2006, Analytica chimica acta.

[30]  Weibiao Zhou,et al.  Design of experiments and regression modelling in food flavour and sensory analysis: A review , 2018 .

[31]  Van-Nam Huynh,et al.  An efficient algorithm for Hiding High Utility Sequential Patterns , 2018, Int. J. Approx. Reason..

[32]  Susan E. Ebeler,et al.  Use of multivariate statistics in understanding wine flavor , 2002 .