Trends and Applications in Knowledge Discovery and Data Mining [electronic resource] : PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14-17, 2019, Revised Selected Papers / edited by Leong Hou U., Hady W. Lauw.
Contributor(s): U., Leong Hou [editor.] | Lauw, Hady W [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Artificial Intelligence: 11607Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019.Description: XIII, 366 p. 162 illus., 115 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030261429.Subject(s): Artificial intelligence | Application software | Data mining | Computer vision | Social sciences -- Data processing | Data protection | Artificial Intelligence | Computer and Information Systems Applications | Data Mining and Knowledge Discovery | Computer Vision | Computer Application in Social and Behavioral Sciences | Data and Information SecurityAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019) -- A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045 -- An Investigation on Multi View based User Behavior towards Spam Detection in Social Networks -- A Cluster Ensemble Strategy for Asian Handicap Betting -- Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example -- Early Churn User Classification in Social Networking Service Using Attention-based Long Short-Term Memory -- PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019) -- Weakly Supervised Learning by a Confusion Matrix of Contexts -- Learning a Semantic Space for Modeling Images,Tags and Feelings in Cross-media Search -- Adversarial Active Learning in the Presence of Weak and Malicious Oracles -- The Most Related Knowledge First: A Progressive Domain Adaptation Method -- Learning Data Representation for Clustering (LDRC 2019) -- Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps -- Deep cascade of extra trees -- Algorithms for an Efficient Tensor Biclustering -- Change point detetion in periodic panel data using a mixture-model-based approach -- The 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining (BDM 2019) -- Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification -- Protein Complexes Detection Based on Deep Neural Network -- Predicting Auction Price of Vehicle License Plate with Deep Residual Learning -- Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions -- Chinese Word Segmentation with Feature Alignment -- Spike Sorting with Locally Weighted Co-association Matrix-based Spectral Clustering -- Label Distribution Learning Based Age-Invariant Face Recognition -- Overall Loss For Deep Neural Networks -- Sentiment Analysis Based on LSTM Architecture with Emoticon Attention -- Aspect Level Sentiment Analysis with Aspect Attention -- The 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer (DLKT 2019) -- Transfer Channel Pruning for Compressing Deep Domain Adaptation Models -- A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting -- Natural Language Business Intelligence Question Answering through SeqtoSeq Transfer Learning -- Robust Faster R-CNN:Increasing Robustness to Occlusions and multi-scale objects -- Effectively Representing Short Text via the Improved Semantic Feature Space Mapping -- Probabilistic Graphical Model Based Highly Scalable Directed Community Detection Algorithm -- Hilltop based recommendation in co-author networks -- Neural Variational Collaborative Filtering for Top-K Recommendation. .
This book constitutes the thoroughly refereed post-workshop proceedings of the workshops that were held in conjunction with the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, in Macau, China, in April 2019. The 31 revised papers presented were carefully reviewed and selected from a total of 52 submissions. They stem from the following workshops: · PAISI 2019: 14th Pacific Asia Workshop on Intelligence and Security Informatics · WeL 2019: PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future · LDRC 2019: PAKDD 2019 Workshop on Learning Data Representation for Clustering · BDM 2019: 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining · DLKT 2019: 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer.
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