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Foundations of intelligent systems = 27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Foundations of intelligent systems/ edited by Annalisa Appice ... [et al.].
其他題名:	27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024 : proceedings /
其他題名:	ISMIS 2024
其他作者:	Appice, Annalisa.
團體作者:	International Symposium on Methodologies for Intelligent Systems
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xix, 316 p. :ill. (some col.), digital ;24 cm.
內容註:	Classification and Clustering. -- Improving the robustness to color perturbations of classification and regression models in the visual evaluation of fruits and vegetables. -- Clustering Under Radius Constraints Using Minimum Dominating Sets. -- Learning Typicality Inclusions in a Probabilistic Description Logic for Concept Combination. -- Neural Network and Natural Language Processing. -- LLMental Classification of mental disorders with large language models. -- CSEPrompts A Benchmark of Introductory Computer Science Prompts. -- Semantically-Informed Domain Adaptation for Named Entity Recognition. -- Token Pruning by Dimensionality Reduction Methods on TCT Colbert for Reranking. -- AI Tools and Models. -- Exploiting microRNA expression data for the diagnosis of disease conditions and the discovery of novel biomarkers. -- HERSE: Handling and Enhancing RDF Summarization through blank node Elimination. -- Rough Sets For a Neuromorphic CMOS System. -- Neural Network and Data Mining. -- Erasing the Shadow Sanitization of Images with Malicious Payloads using Deep Autoencoders. -- Digilog Enhancing Website Embedding on Local Governments - A Comparative Analysis. -- A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery. -- Explainability in AI. -- Enhancing temporal Transformers for financial time series via local surrogate interpretability. -- Explaining commonalities of clusters of RDF resources in natural language. -- Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM) -- Industry Session. -- ScoredKNN: An Efficient KNN Recommender based on Dimensionality Reduction for Big Data. -- Siamese Networks for Unsupervised Failure Detection in Smart Industry. -- Adaptive Forecasting of Extreme Electricity Load. -- Explaining Voltage Control Decisions: A Scenario-Based Approach in Deep Reinforcement Learning. -- Knowledge Graphs for Data Integration in Retail. -- Learning with Complex Data. -- Bayesian Approach for Parameter Estimation in Vehicle Lateral Dynamics. -- Assessing Distance Measures for Change Point Detection in Continual Learning Scenarios. -- SPLindex A Spatial Polygon Learned Index. -- Recommendation Systems and Prediction. -- Action Rules Discovery Leveraging Attributes Correlation Based Vertical Partitioning. -- HalpernSGD A Halpern-inspired Optimizer for Accelerated Neural Network Convergence and Reduced Carbon Footprint. -- Integrating Predictive Process Monitoring Techniques in Smart Agriculture.
Contained By:	Springer Nature eBook
標題:	Expert systems (Computer science) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-62700-2
ISBN:	9783031627002

Foundations of intelligent systems = 27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024 : proceedings /
Foundations of intelligent systems27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024 : proceedings /[electronic resource] :ISMIS 2024edited by Annalisa Appice ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xix, 316 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,146701611-3349 ;. - Lecture notes in computer science ;14670..

Classification and Clustering. -- Improving the robustness to color perturbations of classification and regression models in the visual evaluation of fruits and vegetables. -- Clustering Under Radius Constraints Using Minimum Dominating Sets. -- Learning Typicality Inclusions in a Probabilistic Description Logic for Concept Combination. -- Neural Network and Natural Language Processing. -- LLMental Classification of mental disorders with large language models. -- CSEPrompts A Benchmark of Introductory Computer Science Prompts. -- Semantically-Informed Domain Adaptation for Named Entity Recognition. -- Token Pruning by Dimensionality Reduction Methods on TCT Colbert for Reranking. -- AI Tools and Models. -- Exploiting microRNA expression data for the diagnosis of disease conditions and the discovery of novel biomarkers. -- HERSE: Handling and Enhancing RDF Summarization through blank node Elimination. -- Rough Sets For a Neuromorphic CMOS System. -- Neural Network and Data Mining. -- Erasing the Shadow Sanitization of Images with Malicious Payloads using Deep Autoencoders. -- Digilog Enhancing Website Embedding on Local Governments - A Comparative Analysis. -- A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery. -- Explainability in AI. -- Enhancing temporal Transformers for financial time series via local surrogate interpretability. -- Explaining commonalities of clusters of RDF resources in natural language. -- Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM) -- Industry Session. -- ScoredKNN: An Efficient KNN Recommender based on Dimensionality Reduction for Big Data. -- Siamese Networks for Unsupervised Failure Detection in Smart Industry. -- Adaptive Forecasting of Extreme Electricity Load. -- Explaining Voltage Control Decisions: A Scenario-Based Approach in Deep Reinforcement Learning. -- Knowledge Graphs for Data Integration in Retail. -- Learning with Complex Data. -- Bayesian Approach for Parameter Estimation in Vehicle Lateral Dynamics. -- Assessing Distance Measures for Change Point Detection in Continual Learning Scenarios. -- SPLindex A Spatial Polygon Learned Index. -- Recommendation Systems and Prediction. -- Action Rules Discovery Leveraging Attributes Correlation Based Vertical Partitioning. -- HalpernSGD A Halpern-inspired Optimizer for Accelerated Neural Network Convergence and Reduced Carbon Footprint. -- Integrating Predictive Process Monitoring Techniques in Smart Agriculture.

This book constitutes the proceedings of the 27th International Symposium on Methodologies for Intelligent Systems, ISMIS 2024, held in Poitiers, France, in June 2024. The 18 full papers, 6 short papers and 5 industrial papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers are organized in the following topical sections: Classification and Clustering; Neural Network and Natural Language Processing; AI tools and Models; Neural Network and Data Mining; Explainability in AI; Industry Session; Learning with Complex Data; Recommendation Systems and Prediction.

ISBN: 9783031627002

Standard No.: 10.1007/978-3-031-62700-2doiSubjects--Topical Terms:

572486
Expert systems (Computer science)
--Congresses.

LC Class. No.: QA76.76.E95

Dewey Class. No.: 006.3

Foundations of intelligent systems = 27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024 : proceedings /
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