02110nam 2200481 450 00001420220050718115500.03-540-15691-720030617d1985----km-y0itay0103----baengDEUniversal algebra and lattice theoryproceedings of a conference held at Charleston, July 11-14, 1984edited by Stephen D. ComerBerlin [etc.]Springerc1985VI, 282 p.25 cm.Lecture notes in mathematics11492001Lecture notes in mathematicsAlgebraCongressi512(21. ed.)Algebra, teoria dei numeri03GxxAlgebraic logic06B05Lattices. Structure theory06B20Lattices. Varieties of lattices06B25Lattices. Free lattices, projective lattices, word problems06C05Modular lattices, complemented lattices. Modular lattices, Desarguesian lattices06D10Modular lattices, complemented lattices. Distributive lattices. Complete distributivity08A05General algebraic systems. Algebraic structures. Structure theory08A35General algebraic systems. Algebraic structures. Automorphisms, endomorphisms08B10General algebraic systems. Varieties. Congruence modularity, congruence distributivity08B20General algebraic systems. Varieties. Free algebrasComer,Stephen D.ITUniversità della Basilicata - B.I.A.RICAunimarc000014202Universal algebra and lattice theory79918UNIBASMONSCISCIENZEEXT0020120030617BAS01114020050601BAS011755batch0120050718BAS01105220050718BAS01111120050718BAS01114120050718BAS011155BAS01BAS01BOOKBASA2Polo Tecnico-ScientificoGENCollezione generaleMAT58642S586422003061751Riservati11045nam 2200493 450 99646443520331620231110232133.03-030-73280-0(CKB)4100000011867240(MiAaPQ)EBC6534381(Au-PeEL)EBL6534381(OCoLC)1245674237(PPN)255289391(EXLCZ)99410000001186724020211020d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierIntelligent information and database systems 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7-10, 2021, proceedings /Ngoc Thanh Nguyen [and three others] editorsCham, Switzerland :Springer,[2021]©20211 online resource (xxxi, 867 pages) illustrationsLecture Notes in Computer Science ;v.126723-030-73279-7 Intro -- Preface -- Conference Organization -- Contents -- Data Mining Methods and Applications -- Mining Partially-Ordered Episode Rules in an Event Sequence -- 1 Introduction -- 2 Problem Definition -- 3 The POERM Algorithm -- 4 Experimental Evaluation -- 5 Conclusion -- References -- Investigating Crossover Operators in Genetic Algorithms for High-Utility Itemset Mining -- 1 Introduction -- 2 Preliminaries -- 3 The Headless Chicken Test for HUIM Using GAs -- 4 Experiments and Results -- 4.1 Runtime -- 4.2 Discovered HUIs -- 4.3 Convergence -- 5 Conclusion -- References -- Complexes of Low Dimensional Linear Classifiers with L1 Margins -- 1 Introduction -- 2 Linear Separability of Feature Vectors -- 3 Dual Hyperplanes and Vertices in the Parameter Space -- 4 Perceptron Criterion Function -- 5 Basis Exchange Algorithms -- 6 Reduced Criterion Functions -- 7 Complexes of Linear Classifiers -- 8 Concluding Remarks -- References -- Automatic Identification of Bird Species from Audio -- 1 Introduction -- 2 State of Art -- 2.1 Preprocessing and Feature Extraction -- 2.2 Deep Learning for Sound Classification -- 2.3 Other Approaches -- 3 Our Approach -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 Deep Learning Model Architectures -- 4 Experiments and Evaluation -- 4.1 Evaluation Metrics -- 4.2 Experiments -- 4.3 Best Results -- 5 Conclusions and Future Work -- References -- Session Based Recommendations Using Recurrent Neural Networks - Long Short-Term Memory -- 1 Introduction -- 2 Methods of Content Recommendation -- 2.1 Multi-Layer Perceptron -- 2.2 Autoencoders -- 2.3 Boltzmann Machines -- 3 Evaluation of Recommendation Systems -- 3.1 MAE -- 3.2 MSE -- 3.3 Precision -- 3.4 Recall -- 4 Using the LSTM as a Recommender System -- 4.1 Recurrent Neural Networks -- 4.2 Long Short-Term Memory -- 4.3 Data Preparation -- 4.4 Model Definition.5 Results and Discussions -- 5.1 Experiment -- 5.2 Recall and Precision Results -- 6 Conclusions and Future Work -- References -- UVDS: A New Dataset for Traffic Forecasting with Spatial-Temporal Correlation -- 1 Introduction -- 2 Literature Review -- 2.1 Traffic Forecasting Using Graph Neural Network -- 2.2 Public Traffic Flow Datasets -- 3 UVDS: Urban Vehicle Detection System Dataset -- 3.1 Data Description and Research Challenges -- 3.2 Graph Construction -- 4 Baseline Results and Discussion -- 4.1 Baseline Models -- 4.2 Experimental Results -- 4.3 Open Research Issues Using UVDS Dataset -- 5 Conclusion -- References -- A Parallelized Frequent Temporal Pattern Mining Algorithm on a Time Series Database -- 1 Introduction -- 2 A Frequent Temporal Inter-object Pattern Mining Task -- 3 The Parallelized Frequent Temporal Inter-object Pattern Mining Algorithm on a Time Series Database -- 3.1 BranchTree -- 3.2 From BranchTree to PTP -- 4 Empirical Evaluation -- 5 Conclusion -- References -- An Efficient Approach for Mining High-Utility Itemsets from Multiple Abstraction Levels -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Algorithm -- 5 Evaluation Studies -- 6 Conclusion and Future Work -- References -- Mining Class Association Rules on Dataset with Missing Data -- 1 Introduction -- 2 Related Work -- 2.1 Type of Missing Data -- 2.2 Imputation Method -- 2.3 Mining Class Association Rules -- 3 Model for Mining Class Association Rules with Incomplete Datasets -- 3.1 Definition -- 3.2 Method -- 3.3 Training Process -- 3.4 Application Process -- 4 Experimental Studies -- 5 Conclusion and Future Work -- References -- Machine Learning Methods -- Clustering Count Data with Stochastic Expectation Propagation -- 1 Introduction -- 2 The Exponential-Family Approximation to MSD Distribution -- 3 Stochastic Expectation Propagation.4 EMSD Mixture Model -- 4.1 Clustering Model -- 4.2 Parameter Learning -- 5 Experimental Results -- 5.1 Synthetic Dataset -- 5.2 Sentiment Analysis -- 6 Conclusions -- References -- Entropy-Based Variational Learning of Finite Generalized Inverted Dirichlet Mixture Model -- 1 Introduction -- 2 Model Specification -- 2.1 Finite Generalized Inverted Dirichlet Mixture -- 3 Model Learning with Variational Inference -- 4 Entropy-Based Variational Model Learning -- 4.1 Differential Entropy Estimation -- 4.2 MeanNN Entropy Estimator -- 5 Experimental Results -- 5.1 Breast Cancer -- 5.2 Image Analysis -- 6 Conclusion -- References -- Mixture-Based Unsupervised Learning for Positively Correlated Count Data -- 1 Introduction -- 2 Negative Multinomial Mixture Model -- 2.1 Maximum Likelihood Parameter Estimation -- 3 Model Selection -- 4 Experimental Results -- 5 Conclusion -- References -- Phase Prediction of Multi-principal Element Alloys Using Support Vector Machine and Bayesian Optimization -- 1 Introduction -- 2 Description of Datasets -- 3 Building Prediction Models with SVM -- 3.1 Defining Predictors and an Outcome -- 3.2 Tuning Hyperparameters Using Bayesian Optimization -- 3.3 Cross-Validation of Prediction Models Employing Tuned Hyperparameters -- 4 Statistical Analysis of Experimental Results -- 5 Conclusions -- References -- VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning -- 1 Introduction -- 2 Background and Related Work -- 2.1 Ensemble Learning and Ensemble Selection -- 2.2 Variable Learning Encoding in Evolutionary Computation -- 3 Proposed Method -- 3.1 Ensemble Selection for Deep Ensemble Systems -- 3.2 Optimization Problems and Algorithm -- 4 Experimental Studies -- 4.1 Experimental Settings -- 4.2 Comparison to the Benchmark Algorithms -- 4.3 Discussions -- 5 Conclusions -- References.Demand Forecasting for Textile Products Using Statistical Analysis and Machine Learning Algorithms -- 1 Introducción -- 2 Related Works -- 3 Materials and Methods -- 3.1 Case Study Description -- 3.2 Statistical Analysis -- 3.3 Demand Forecasting -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Parallelization of Reinforcement Learning Algorithms for Video Games -- 1 Introduction -- 2 Background and Related Work -- 2.1 Reinforcement Learning -- 2.2 Methods for Solving RL Problems -- 2.3 Parallelization of RL Methods -- 3 Experiment -- 3.1 Environment and Algorithms Parameters -- 3.2 Measures -- 4 Results -- 4.1 Influence of Parallelization on Training Times -- 4.2 Throughput Measurements -- 4.3 System Performance Measurements -- 5 Conclusions -- References -- Decision Support and Control Systems -- A Gap-Based Memetic Differential Evolution (GaMeDE) Applied to Multi-modal Optimisation - Using Multi-objective Optimization Concepts -- 1 Introduction -- 2 Contribution and Motivation -- 3 Approach -- 3.1 Archive Management -- 3.2 Gap Selection Operator -- 3.3 Two-Phased GaMeDE -- 3.4 Clustering -- 3.5 Local Optimization -- 4 Experiments -- 4.1 Setup -- 4.2 Metrics -- 4.3 Results -- 4.4 Discussion -- 5 Conclusions -- References -- Simulating Emergency Departments Using Generalized Petri Nets -- 1 Introduction -- 2 Modelling Approach -- 2.1 Data Collection and Processing -- 2.2 Simulation Model -- 3 Simulation Modeling -- 3.1 The Proposed GSPN-Based Model -- 3.2 The Hierarchical GSPN Model of the ED -- 4 Simulation Results and Discussion -- 4.1 Model Validation -- 4.2 Forecasting Patients' Waiting Times -- 5 Conclusion -- References -- What Do You Know About Your Network: An Empirical Study of Value Network Awareness in E-commerce -- 1 Introduction -- 2 Theoretical Background -- 2.1 Value Network -- 2.2 Network Awareness.3 Overview of the Studies -- 3.1 Sampling of Study 1 - Suppliers and Complementors -- 3.2 Sampling of Study 2 - Online Sellers -- 3.3 Sampling of Study 3 - End Customers -- 4 Results -- 5 Discussion -- 6 Limitations and Future Research -- References -- A Robust Approach to Employee Competences in Project Management -- 1 Introduction -- 2 Illustrative Example -- 3 Model of Employee Competence Configuration Problem -- 4 Method for Verifying the Set of Employee Competences -- 5 Computational Examples -- 6 Conclusions -- References -- Key Aspects of Customer Intelligence in the Era of Massive Data -- 1 Introduction -- 2 Literature Review -- 2.1 Research Process -- 2.2 The Revolution of Customer Intelligence -- 3 Theoretical Framework -- 3.1 Resource-Based Theory -- 3.2 A Resource-Based Framework of Customer Intelligence Management -- 4 Key Aspects of Customer Intelligence in the Era of Massive Data -- 4.1 Product/Service Aspect -- 4.2 Price Aspect -- 4.3 Promotion Aspect -- 4.4 Place Aspect -- 4.5 People Aspect -- 4.6 Process Aspect -- 4.7 Physical Evidence Aspect -- 5 Conclusion -- References -- How Spatial Data Analysis Can Make Smart Lighting Smarter -- 1 Introduction -- 2 Problem Statement -- 3 Methodology -- 4 Implementation -- 4.1 Mapping of Linestrings to Road Shapes -- 4.2 Assignment of Lights to Lit Areas -- 5 Results -- 5.1 Quality of Modelled Situations -- 5.2 Estimation Efficiency -- 6 Conclusions -- References -- Natural Language Processing -- Convolutional Neural Networks for Web Documents Classification -- 1 Introduction -- 2 Related Work -- 3 Text Classification -- 4 Methodology -- 4.1 Dataset -- 4.2 Model -- 4.3 Evaluation -- 5 Experimental Results -- 5.1 Baseline Setup -- 5.2 Multi-class Problem -- 5.3 Input Variation -- 5.4 Embedding Vectors Variation -- 5.5 Language Transfer Learning -- 6 Conclusions -- References.Sequential Model-Based Optimization for Natural Language Processing Data Pipeline Selection and Optimization.Lecture Notes in Computer Science Expert systems (Computer science)CongressesExpert systems (Computer science)006.33Nguyen Ngoc Thanh(Computer scientist),MiAaPQMiAaPQMiAaPQBOOK996464435203316Intelligent Information and Database Systems1902355UNISA