東華大學圖書館 |

Discovery science = 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Discovery science/ edited by Carlos Soares, Luis Torgo.
Reminder of title:	24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings /
remainder title:	DS 2021
other author:	Soares, Carlos.
corporate name:	International Conference on Discovery Science
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xii, 474 p. :ill., digital ;24 cm.
[NT 15003449]:	Applications -- Automated Grading of Exam Responses: An Extensive Classification Benchmark -- Automatic human-like detection of code smells -- HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM -- Predicting reach to find persuadable customers: improving uplift models for churn prevention -- Classification -- A Semi-Supervised Framework for Misinformation Detection -- An Analysis of Performance Metrics for Imbalanced Classification -- Combining Predictions under Uncertainty: The Case of Random Decision Trees -- Shapley-Value Data Valuation for Semi-Supervised Learning -- Data streams -- A Network Intrusion Detection System for Concept Drifting Network Traffic Data -- Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams -- Statistical Analysis of Pairwise Connectivity -- Graph and Network Mining -- FHA: Fast Heuristic Attack against Graph Convolutional Networks -- Ranking Structured Objects with Graph Neural Networks -- Machine Learning for COVID-19 -- Knowledge discovery of the delays experienced in reporting covid19 confirmed positive cases using time to event models -- Multi-Scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data -- Prioritization of COVID-19 literature via unsupervised keyphrase extraction and document representation learning -- Sentiment Nowcasting during the COVID-19 Pandemic -- Neural Networks and Deep Learning -- A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data -- Calibrated Resampling for Imbalance and Long-Tails in Deep learning -- Consensus Based Vertically Partitioned Multi-Layer Perceptrons for Edge Computing -- Controlling BigGAN Image Generation with a Segmentation Network -- GANs for tabular healthcare data generation: a review on utility and privacy -- Preferences and Recommender Systems -- An Ensemble Hypergraph Learning framework for Recommendation -- KATRec: Knowledge Aware aTtentive Sequential Recommendations -- Representation Learning and Feature Selection -- Elliptical Ordinal Embedding -- Unsupervised Feature Ranking via Attribute Networks -- Responsible Artificial Intelligence -- Deriving a Single Interpretable Model by Merging Tree-based Classifiers -- Ensemble of Counterfactual Explainers. Riccardo Guidotti and Salvatore Ruggieri -- Learning Time Series Counterfactuals via Latent Space Representations -- Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems -- Local Interpretable Classifier Explanations with Self-generated Semantic Features -- Privacy risk assessment of individual psychometric profiles -- The Case for Latent Variable vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19 -- Spatial, Temporal and Spatiotemporal Data -- Local Exceptionality Detection in Time Series Using Subgroup Discovery -- Neural Additive Vector Autoregression Models for Causal Discovery in Time Series -- Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data.
Contained By:	Springer Nature eBook
Subject:	Science - Philosophy -
Online resource:	https://doi.org/10.1007/978-3-030-88942-5
ISBN:	9783030889425

Discovery science = 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings /
Discovery science24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings /[electronic resource] :DS 2021edited by Carlos Soares, Luis Torgo. - Cham :Springer International Publishing :2021. - xii, 474 p. :ill., digital ;24 cm. - Lecture notes in computer science,129860302-9743 ;. - Lecture notes in computer science ;12986..

Applications -- Automated Grading of Exam Responses: An Extensive Classification Benchmark -- Automatic human-like detection of code smells -- HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM -- Predicting reach to find persuadable customers: improving uplift models for churn prevention -- Classification -- A Semi-Supervised Framework for Misinformation Detection -- An Analysis of Performance Metrics for Imbalanced Classification -- Combining Predictions under Uncertainty: The Case of Random Decision Trees -- Shapley-Value Data Valuation for Semi-Supervised Learning -- Data streams -- A Network Intrusion Detection System for Concept Drifting Network Traffic Data -- Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams -- Statistical Analysis of Pairwise Connectivity -- Graph and Network Mining -- FHA: Fast Heuristic Attack against Graph Convolutional Networks -- Ranking Structured Objects with Graph Neural Networks -- Machine Learning for COVID-19 -- Knowledge discovery of the delays experienced in reporting covid19 confirmed positive cases using time to event models -- Multi-Scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data -- Prioritization of COVID-19 literature via unsupervised keyphrase extraction and document representation learning -- Sentiment Nowcasting during the COVID-19 Pandemic -- Neural Networks and Deep Learning -- A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data -- Calibrated Resampling for Imbalance and Long-Tails in Deep learning -- Consensus Based Vertically Partitioned Multi-Layer Perceptrons for Edge Computing -- Controlling BigGAN Image Generation with a Segmentation Network -- GANs for tabular healthcare data generation: a review on utility and privacy -- Preferences and Recommender Systems -- An Ensemble Hypergraph Learning framework for Recommendation -- KATRec: Knowledge Aware aTtentive Sequential Recommendations -- Representation Learning and Feature Selection -- Elliptical Ordinal Embedding -- Unsupervised Feature Ranking via Attribute Networks -- Responsible Artificial Intelligence -- Deriving a Single Interpretable Model by Merging Tree-based Classifiers -- Ensemble of Counterfactual Explainers. Riccardo Guidotti and Salvatore Ruggieri -- Learning Time Series Counterfactuals via Latent Space Representations -- Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems -- Local Interpretable Classifier Explanations with Self-generated Semantic Features -- Privacy risk assessment of individual psychometric profiles -- The Case for Latent Variable vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19 -- Spatial, Temporal and Spatiotemporal Data -- Local Exceptionality Detection in Time Series Using Subgroup Discovery -- Neural Additive Vector Autoregression Models for Causal Discovery in Time Series -- Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data.

This book constitutes the proceedings of the 24th International Conference on Discovery Science, DS 2021, which took place virtually during October 11-13, 2021. The 36 papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topical sections named: applications; classification; data streams; graph and network mining; machine learning for COVID-19; neural networks and deep learning; preferences and recommender systems; representation learning and feature selection; responsible artificial intelligence; and spatial, temporal and spatiotemporal data.

ISBN: 9783030889425

Standard No.: 10.1007/978-3-030-88942-5doiSubjects--Topical Terms:

526932
Science
--Philosophy

LC Class. No.: Q174 / .I5625 2021

Dewey Class. No.: 501

Discovery science = 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings /
LDR:04868nmm a2200361 a 4500 001 2253529
003 DE-He213
005 20211008074640.0
006 m d
007 cr nn 008maaau
008 220327s2021 sz s 0 eng d
020 $a 9783030889425 $q (electronic bk.)
020 $a 9783030889418 $q (paper)
024 7 $a 10.1007/978-3-030-88942-5 $2 doi
035 $a 978-3-030-88942-5
040 $a GP $c GP
041 0 $a eng
050 4 $a Q174 $b .I5625 2021
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 501 $2 23
090 $a Q174 $b .I61 2021
111 2 $a International Conference on Discovery Science $n (24th : $d 2021 : $c Online) $3 3521787
245 1 0 $a Discovery science $h [electronic resource] : $b 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021 : proceedings / $c edited by Carlos Soares, Luis Torgo.
246 3 $a DS 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xii, 474 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 12986
490 1 $a Lecture notes in artificial intelligence
505 0 $a Applications -- Automated Grading of Exam Responses: An Extensive Classification Benchmark -- Automatic human-like detection of code smells -- HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM -- Predicting reach to find persuadable customers: improving uplift models for churn prevention -- Classification -- A Semi-Supervised Framework for Misinformation Detection -- An Analysis of Performance Metrics for Imbalanced Classification -- Combining Predictions under Uncertainty: The Case of Random Decision Trees -- Shapley-Value Data Valuation for Semi-Supervised Learning -- Data streams -- A Network Intrusion Detection System for Concept Drifting Network Traffic Data -- Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams -- Statistical Analysis of Pairwise Connectivity -- Graph and Network Mining -- FHA: Fast Heuristic Attack against Graph Convolutional Networks -- Ranking Structured Objects with Graph Neural Networks -- Machine Learning for COVID-19 -- Knowledge discovery of the delays experienced in reporting covid19 confirmed positive cases using time to event models -- Multi-Scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data -- Prioritization of COVID-19 literature via unsupervised keyphrase extraction and document representation learning -- Sentiment Nowcasting during the COVID-19 Pandemic -- Neural Networks and Deep Learning -- A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data -- Calibrated Resampling for Imbalance and Long-Tails in Deep learning -- Consensus Based Vertically Partitioned Multi-Layer Perceptrons for Edge Computing -- Controlling BigGAN Image Generation with a Segmentation Network -- GANs for tabular healthcare data generation: a review on utility and privacy -- Preferences and Recommender Systems -- An Ensemble Hypergraph Learning framework for Recommendation -- KATRec: Knowledge Aware aTtentive Sequential Recommendations -- Representation Learning and Feature Selection -- Elliptical Ordinal Embedding -- Unsupervised Feature Ranking via Attribute Networks -- Responsible Artificial Intelligence -- Deriving a Single Interpretable Model by Merging Tree-based Classifiers -- Ensemble of Counterfactual Explainers. Riccardo Guidotti and Salvatore Ruggieri -- Learning Time Series Counterfactuals via Latent Space Representations -- Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems -- Local Interpretable Classifier Explanations with Self-generated Semantic Features -- Privacy risk assessment of individual psychometric profiles -- The Case for Latent Variable vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19 -- Spatial, Temporal and Spatiotemporal Data -- Local Exceptionality Detection in Time Series Using Subgroup Discovery -- Neural Additive Vector Autoregression Models for Causal Discovery in Time Series -- Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data.
520 $a This book constitutes the proceedings of the 24th International Conference on Discovery Science, DS 2021, which took place virtually during October 11-13, 2021. The 36 papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topical sections named: applications; classification; data streams; graph and network mining; machine learning for COVID-19; neural networks and deep learning; preferences and recommender systems; representation learning and feature selection; responsible artificial intelligence; and spatial, temporal and spatiotemporal data.
650 0 $a Science $x Philosophy $x Congresses. $3 526932
650 0 $a Discoveries in science $v Congresses. $3 870826
650 0 $a Research $x Automation $v Congresses. $3 3258755
650 0 $a Machine learning $x Congresses. $3 576368
650 0 $a Data mining $v Congresses. $3 551626
650 1 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 892702
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Computer Communication Networks. $3 775497
650 2 4 $a Computers and Education. $3 892757
700 1 $a Soares, Carlos. $3 3521788
700 1 $a Torgo, Luis. $3 3521789
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 12986. $3 3521790
830 0 $a Lecture notes in artificial intelligence. $3 3382562
856 4 0 $u https://doi.org/10.1007/978-3-030-88942-5
950 $a Computer Science (SpringerNature-11645)