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[null,"1.","Record Nr.",null,"UNISA996490360703316"]
[null,null,"Autore",null,"Nguyen Ngoc Thanh (Computer scientist)"]
[null,null,"Titolo",null,"Computational Collective Intelligence : 14th International Conference, ICCCI 2022, Hammamet, Tunisia, September 28-30, 2022, Proceedings"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing AG, , 2022"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-16014-2"]
[null,null,"Descrizione fisica",null,"1 online resource (863 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; v.13501"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Collective Intelligence and Collective Decision-Making -- Inferring Event Causality in Films via Common Knowledge Corpora -- 1 Introduction -- 1.1 Background -- 1.2 Research Objectives and Contributions -- 2 Background and Related Work -- 2.1 Event Causality in Films -- 2.2 Computational Methods -- 3 Event Causality Inference System -- 4 Evaluation Experiments -- 5 Discussion -- References -- Cooperation Game on Communication Multigraph with Fuzzy Parameters -- 1 Introduction -- 2 Preliminaries -- 3 Concept of the FUZZY Value of the Sub-additive Cooperative Game on Communication Multigraph with Fuzzy Capacities -- 4 Concept of the FUZZY Value of the Sub-additive Cooperative Game on Communication Multigraph with Fuzzy Capacities and Fuzzy Goal -- 5 Conclusions and Future Works -- References -- Impact of Similarity Measure on the Quality of Communities Detected in Social Network by Hierarchical Clustering -- 1 Introduction -- 2 Organizational Social Networks -- 3 Community Detection Problem -- 4 Hierarchical Clustering Approach to the Community Detection -- 4.1 Hierarchical Clustering -- 4.2 Similarity Measures in Social Networks -- 4.3 Hierarchical Clustering Approach to the Community Detection in Organizational Social Network -- 5 Computational Experiment -- 6 Conclusions -- References -- An Approach to Modeling a Real-Time Updated Environment Based on Messages from Agents -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Environment Model Assumptions -- 3.2 Environment Model -- 4 Case Study: AriaDNA Life System -- 4.1 Space and Dimensions -- 4.2 Entity Types -- 4.3 Messages -- 4.4 Interactions -- 5 Summary -- References "]
[{"$nulls":4},"-- Updating the Result Ontology Integration at the Concept Level in the Event of the Evolution of Their Components -- 1 Introduction -- 2 Related Works."]
[{"$nulls":4},"3 Basic Notions -- 4 Methods of Updating Integrated Ontologies -- 4.1 Updating Results of Ontology Integration After Concept Removal -- 4.2 Updating Results of Ontology Integration After Adding New Concepts -- 4.3 Updating Results of Ontology Integration After Concepts Modification -- 5 Experimental Evaluation -- 6 Summary -- References -- Integrating Machine Learning into Learner Profiling for Adaptive and Gamified Learning System -- 1 Introduction -- 2 Proposed Method -- 2.1 Functional Architecture -- 3 Experimentation and Results -- 3.1 Used Method -- 3.2 Results -- 4 Conclusion -- References -- Deep Learning Techniques -- A New Deep Learning Fusion Approach for Emotion Recognition Based on Face and Text -- 1 Introduction -- 2 Facial-Textual Emotion Recognition (FTxER) Architecture -- 3 Results and Discussion -- 4 Conclusion and Future Work -- References -- Cycle Route Signs Detection Using Deep Learning -- 1 Introduction -- 2 Problem Definition -- 2.1 Car License Plate Recognition and Reading -- 2.2 Real-time Traffic Sign Detection Using CNN -- 3 Solution -- 3.1 YOLO -- 3.2 OCR -- 4 Implementation -- 4.1 Technologies Used -- 4.2 Data Training -- 4.3 Applications -- 5 Testing of Developed Application -- 6 Conclusion -- References -- Data Augmentation for Morphological Analysis of Histopathological Images Using Deep Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Methods -- 2.3 Morphing Concept -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- An End-to-End Framework for Evaluating Explainable Deep Models: Application to Historical Document Image Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 4 Experiments and Results -- 4.1 Experimental Corpus -- 4.2 Implementation Details -- 4.3 Results -- 5 Conclusions and Further Work -- References."]
[{"$nulls":4},"Deep Convolutional Neural Network for Arabic Speech Recognition -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 3.1 Convolutional Neural Network (CNN) -- 3.2 LSTM -- 4 Experimental Results and Discussion -- 4.1 Datasets and Input Features -- 4.2 Results and Discussion -- 5 Conclusion and Future Works -- References -- RingNet: Geometric Deep Representation Learning for 3D Multi-domain Protein Shape Retrieval -- 1 Introduction -- 2 Related Works -- 3 RingNet Neural Network -- 3.1 Descriptors Calculation -- 3.2 RingNet Layer -- 3.3 Fusion Layer -- 4 Experimental Results -- 4.1 Dataset and Metrics -- 4.2 3D Protein Shape Classification -- 4.3 3D Protein Shape Retrieval -- 5 Conclusion -- References -- Patch Selection for Melanoma Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Description and Preprocessing -- 2.2 Entropy -- 2.3 Mean Exhaustive Minimum Distance (MEMD) Criterion -- 2.4 Network Architecture -- 3 Experimental Results -- 4 Conclusion -- References -- Natural Language Processing -- Multi-model Analysis of Language-Agnostic Sentiment Classification on MultiEmo Data -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 3.1 Pipeline -- 3.2 MultiEmo Dataset -- 3.3 Scenarios -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Sentiment Analysis of Tunisian Users on Social Networks: Overcoming the Challenge of Multilingual Comments in the Tunisian Dialect -- Abstract -- 1 Introduction -- 2 Specificities of Tunisian Dialect Sentiment Analysis -- 2.1 The Use of Multilingual Vocabulary -- 2.2 The Phenomenon of Linguistic Code-switching -- 3 Background and Related Work -- 3.1 Arabic Dialects Sentiment Analysis -- 3.2 Tunisian Dialect Sentiment Analysis -- 3.3 Discussion -- 4 Proposed Methodology -- 4.1 Data "]
[{"$nulls":4},"Collection -- 4.2 Data Preprocessing -- 4.3 Model Training."]
[{"$nulls":4},"5 Experiments and Results -- 5.1 Baseline -- 5.2 Dataset -- 5.3 Experimental Results -- 5.4 Discussion -- 6 Conclusion -- Acknowledgment -- References -- Non-Contextual vs Contextual Word Embeddings in Multiword Expressions Detection -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Non-Contextual Dataset -- 3.2 Contextual Dataset -- 4 Methods for Multiword Expression Detection -- 5 Experiments -- 6 Results -- 7 Discussion -- 8 Conclusions and Future Work -- References -- Context-free Transformer-based Generative Lemmatiser for Polish -- 1 Introduction -- 2 Related Works -- 2.1 Contextual Lemmatisation -- 2.2 Context-free Lemmatisation -- 2.3 Lemmatisation for the Polish Language -- 3 Problem Description -- 4 Architecture -- 4.1 Transformer-based Lemmatiser -- 5 Experiments -- 6 Conclusions -- References -- French Object Clitics in the Interlanguage: A Linguistic Description and a Formal Analysis in the ACCG Framework -- 1 Introduction -- 2 Interlanguage -- 2.1 The Concept -- 2.2 French Object Clitics in the Interlanguage -- 3 Applicative Combinatory Categorical Grammar -- 4 Object Clitics by Means of ACCG -- 5 Conclusion -- References -- Contradiction Detection Approach Based on Semantic Relations and Evidence of Uncertainty -- 1 Introduction -- 2 Related Work -- 3 Motivation and Proposed Model -- 3.1 Motivation -- 3.2 Description of the Approach -- 4 Semantic Construction of a Sentence -- 4.1 Pretreatment -- 4.2 Concept Extraction -- 4.3 Extraction of Uncertainty Expressions -- 4.4 Calculation of Degree of Uncertainty -- 4.5 Extraction of Binary Relations -- 5 Contradiction Assessment -- 5.1 Detection of Opposing Information -- 5.2 Detection of Contradiction -- 6 Experimental Evaluation -- 6.1 Test Environment -- 6.2 Experiments and Results -- 7 Conclusion -- References -- C-DESERT Score for Arabic Text Summary Evaluation -- Abstract."]
[{"$nulls":4},"1 Introduction -- 2 Related works -- 3 Proposed method -- 3.1 Document Embedding Model -- 3.2 Building the Doc2Vec Model -- 3.3 Features -- 3.4 Combination Scheme -- 4 Experiments -- 4.1 Data Sets -- 4.2 Result -- 5 Conclusion -- References -- Data Mining and Machine Learning -- Proficiency Level Classification of Foreign Language Learners Using Machine Learning Algorithms and Multilingual Models -- 1 Introduction -- 2 Related Works -- 3 Experiments -- 3.1 Datasets -- 3.2 Features -- 3.3 Methods -- 3.4 Tool Implementation -- 3.5 Experiment Scenarios -- 4 Results and Analysis -- 4.1 Experiment One -- 4.2 Experiment Two -- 4.3 Experiment Three -- 5 Conclusions -- References -- Simulation System for Producing Real World Dataset to Predict the Covid-19 Contamination Process⋆ -- 1 Introduction -- 2 Contact Tracing -- 2.1 GPS Accuracy -- 2.2 Bluetooth LE Distance Measurement -- 2.3 WiFi -- 2.4 Zigbee -- 2.5 Comparing Technologies -- 3 Dataset Collection -- 3.1 Simulating Real World Scene -- 4 Processing Data -- 4.1 Graph Modeling -- 4.2 Retrieving Basic Statistics -- 4.3 Graph Data Science Algorithms -- 5 Conclusion -- References -- Design and Compression Study for Convolutional Neural Networks Based on Evolutionary Optimization for Thoracic X-Ray Image Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 CNN Design -- 3.2 CNN Compression -- 4 Experiments -- 4.1 Expirement Configuration and Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- TF-MOPNAS: Training-free Multi-objective Pruning-Based Neural Architecture Search -- 1 Introduction -- 2 Background and Related Works -- 2.1 Progressive Search Space Shrinking and Architecture Selection -- 2.2 Training-free Metrics in Pruning-based NAS -- 3 Training-free Multi-objective Pruning-based Neural Architecture Search -- 4 Experiments "]
[{"$nulls":4},"and Results."]
[{"$nulls":4},"4.1 Results on NAS-Bench-101."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 14th International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022.The 56 full papers and 10 short papers were carefully reviewed and selected from 420 submissions. The papers are grouped in topical sections on collective intelligence and collective decision-making; deep learning techniques; natural language processing; data minning and machine learning; knowledge engineering and semantic web; computer vision techniques; social networks and intelligent systems; cybersecurity and internet of things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; applications for industry 4.0."]