UID:
almahu_9949407265602882
Format:
XXII, 537 p. 172 illus., 143 illus. in color.
,
online resource.
Edition:
1st ed. 2022.
ISBN:
9783031220647
Series Statement:
Lecture Notes in Artificial Intelligence, 13725
Content:
The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Note:
Finance and Healthcare -- Application of Supplemental Sampling and Interpretable AI in Credit Scoring for Canadian Fintechs: Methods and Case Studies -- A Deep Convolutional Autoencoder-based Approach for Parkinson's Disease Diagnosis Through Speech Signals -- Mining the Potential Relationships Between Cancer Cases and Industrial Pollution Based on High-influence Ordered-pair Patterns -- Finding Hidden Relationships Between Medical Concepts By Leveraging Metamap And Text Mining Techniques -- Causality Discovery Based on Combined Causes and Multiple Causes in Drug-drug Interaction -- An Integrated Medical Recommendation Mechanism Combining Promote Product Singular Value Decomposition and Knowledge Graph -- Web and IoT Applications -- Joint Extraction of Entities and Relations in The News Domain -- Event Detection From Web Data in Chinese Based on Bi-LSTM with Attention -- Sentiment Analysis of Tweets Using Deep Learning -- Cyber Attack Detection in IoT Networks with Small Samples: Implementation and Analysis -- SATB: A Testbed of IoT-based Smart Agriculture Network for Dataset Generation -- An Overview on Reducing Social Networks' Size -- AuCM: Course Map Data Analytics for Australian IT Programs in Higher Education -- Profit Maximization using Social Networks in Two-Phase Setting -- On-device Application -- SESA: Fast Trajectory Compression Method Using Sub-trajectories Segmented by Stay Areas -- Android Malware Detection Based on Stacking and Multi-feature Fusion -- In uential Billboard Slot Selection using Pruned Submodularity Graph -- Quantifying Association Between Street-Level Urban Features and Crime Distribution Around Manhattan Subway Entrances -- The Coherence and Divergence Between the Objective and Subjective Measurements of Street Perceptions for Shanghai -- Other Applications -- A Comparative Study of Question Answering over Knowledge Bases -- A Deep Learning Framework for Removing Bias from Single-Photon Emission Computerized Tomography -- Popularity Forecasting for Emerging Research Topics at its Early Stage of Evolution -- Positive Unlabeled Learning by Sample Selection and Prototype Refinement -- Handling missing data with Markov boundary -- Pattern Mining -- An Efficient Method for outlying Aspect Mining based on Genetic Algorithm -- Effective Mining of Contrast Hybrid Patterns from Nominal-numerical Mixed Data -- TPFL: Test Input Prioritization for Deep Neural Networks Based on Fault Localization -- Mining Maximal Sub-prevalent Co-location Patterns Based on k-hop -- An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns -- Mining E-closed High Utility Co-location Patterns From Spatial Data -- Graph Mining -- Implementation and Analysis of Centroid Displacement based k-Nearest Neighbors -- EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain -- Deterministic Graph-Walking Program Mining -- A Benchmarking Evaluation of Graph Neural Networks on Traffic Speed Prediction -- Multi-view Gated Graph Convolutional Network for Aspect-Level Sentiment Classification -- Decentralized Graph Processing for Reachability Queries -- Being Automated or Not? Risk Identification of Occupations with Graph Neural Networks.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031220630
Additional Edition:
Printed edition: ISBN 9783031220654
Language:
English
DOI:
10.1007/978-3-031-22064-7
URL:
https://doi.org/10.1007/978-3-031-22064-7
