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Advances in knowledge discovery and data mining : 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings. Part V / De-Nian Yang, Xing Xie, Vincent S. Tseng, Jian Pei, Jen-Wei Huang, Jerry Chun-Wei Lin, editors.

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science. Lecture notes in artificial intelligence. | Lecture notes in computer science ; 14649. | LNCS sublibrary. SL 7, Artificial intelligence.Publisher: Singapore : Springer, 2024Description: 1 online resource (xxxiv, 404 pages) : illustrations (some color)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789819722624
  • 9819722624
Other title:
  • PAKDD 2024
Subject(s): DDC classification:
  • 006.3/12 23/eng/20240501
LOC classification:
  • QA76.9.D343
Online resources:
Contents:
Intro -- General Chairs' Preface -- PC Chairs' Preface -- Organization -- Contents - Part V -- Multimedia and Multimodal Data -- Re-thinking Human Activity Recognition with Hierarchy-Aware Label Relationship Modeling -- 1 Introduction -- 2 Related Work -- 2.1 Human Activity Recognition (HAR) -- 2.2 Hierarchical Label Modeling -- 3 Problem Formulation -- 4 Our Proposals -- 4.1 Hierarchy-Aware Label Encoding -- 4.2 Activity Data Encoding -- 4.3 Label-Data Joint Embedding Learning -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Experimental Results -- 5.3 Ablation Study
6 Discussions and Conclusion -- References -- Geometrically-Aware Dual Transformer Encoding Visual and Textual Features for Image Captioning -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Features Extractor -- 3.2 Caption Generator -- 3.3 Attention Block -- 3.4 Training and Objectives -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Experiment Result -- 5 Conclusions -- References -- MHDF: Multi-source Heterogeneous Data Progressive Fusion for Fake News Detection -- 1 Introduction -- 2 Related Work -- 3 MHDF Model -- 3.1 Model Overview
3.2 Multi-source Heterogeneous Data Amplification -- 3.3 News Textual Feature Fusion -- 3.4 News Visual Feature Fusion -- 3.5 Sentiment Feature Extractor -- 3.6 Feature Integration Classifier -- 4 Experiments -- 4.1 Dataset -- 4.2 Experimental Settings -- 4.3 Performance Comparison -- 4.4 Ablation Experiments and Validity Verification -- 4.5 Conclusions -- References -- Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-Based Curriculum Learning -- 1 Introduction -- 2 Related Works -- 2.1 Automatic Speech Recognition Methods
2.2 Connectionist Temporal Classification (CTC) Loss -- 3 Proposed Method -- 3.1 Multiple Hypotheses for Unlabeled Instances -- 3.2 Training ASR Model with Multiple Hypotheses -- 3.3 Curriculum Learning -- 3.4 Theoretical Analysis -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Transcription Performance (Q1) -- 4.3 Speed of Convergence (Q2) -- 4.4 Ablation Study (Q3) -- 5 Conclusions -- References -- MM-PhyQA: Multimodal Physics Question-Answering with Multi-image CoT Prompting -- 1 Introduction -- 2 Related Works -- 2.1 Available Datasets -- 2.2 Large Multimodal Models and Chain-of-Thought
3 Novel Dataset -- 3.1 Original Dataset Creation -- 3.2 Data Augmentation Procedure -- 3.3 Chain of Thought Variant -- 3.4 MM-PhyQA Dataset Topics -- 4 Methodology -- 4.1 Multi-image Chain-of-Thought (MI-CoT) -- 5 Experiments -- 5.1 Models -- 6 Results and Discussion -- 6.1 Model Performance -- 6.2 Zero Shot Prompting Vs Supervised Fine-Tuning -- 6.3 Effect of Chain of Thought Prompting -- 6.4 Error Analysis -- 7 Conclusion -- References -- Adversarial Text Purification: A Large Language Model Approach for Defense -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Large Language Models
Summary: The 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7-10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Holdings
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The 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7-10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed May 1, 2024).

Intro -- General Chairs' Preface -- PC Chairs' Preface -- Organization -- Contents - Part V -- Multimedia and Multimodal Data -- Re-thinking Human Activity Recognition with Hierarchy-Aware Label Relationship Modeling -- 1 Introduction -- 2 Related Work -- 2.1 Human Activity Recognition (HAR) -- 2.2 Hierarchical Label Modeling -- 3 Problem Formulation -- 4 Our Proposals -- 4.1 Hierarchy-Aware Label Encoding -- 4.2 Activity Data Encoding -- 4.3 Label-Data Joint Embedding Learning -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Experimental Results -- 5.3 Ablation Study

6 Discussions and Conclusion -- References -- Geometrically-Aware Dual Transformer Encoding Visual and Textual Features for Image Captioning -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Features Extractor -- 3.2 Caption Generator -- 3.3 Attention Block -- 3.4 Training and Objectives -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Experiment Result -- 5 Conclusions -- References -- MHDF: Multi-source Heterogeneous Data Progressive Fusion for Fake News Detection -- 1 Introduction -- 2 Related Work -- 3 MHDF Model -- 3.1 Model Overview

3.2 Multi-source Heterogeneous Data Amplification -- 3.3 News Textual Feature Fusion -- 3.4 News Visual Feature Fusion -- 3.5 Sentiment Feature Extractor -- 3.6 Feature Integration Classifier -- 4 Experiments -- 4.1 Dataset -- 4.2 Experimental Settings -- 4.3 Performance Comparison -- 4.4 Ablation Experiments and Validity Verification -- 4.5 Conclusions -- References -- Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-Based Curriculum Learning -- 1 Introduction -- 2 Related Works -- 2.1 Automatic Speech Recognition Methods

2.2 Connectionist Temporal Classification (CTC) Loss -- 3 Proposed Method -- 3.1 Multiple Hypotheses for Unlabeled Instances -- 3.2 Training ASR Model with Multiple Hypotheses -- 3.3 Curriculum Learning -- 3.4 Theoretical Analysis -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Transcription Performance (Q1) -- 4.3 Speed of Convergence (Q2) -- 4.4 Ablation Study (Q3) -- 5 Conclusions -- References -- MM-PhyQA: Multimodal Physics Question-Answering with Multi-image CoT Prompting -- 1 Introduction -- 2 Related Works -- 2.1 Available Datasets -- 2.2 Large Multimodal Models and Chain-of-Thought

3 Novel Dataset -- 3.1 Original Dataset Creation -- 3.2 Data Augmentation Procedure -- 3.3 Chain of Thought Variant -- 3.4 MM-PhyQA Dataset Topics -- 4 Methodology -- 4.1 Multi-image Chain-of-Thought (MI-CoT) -- 5 Experiments -- 5.1 Models -- 6 Results and Discussion -- 6.1 Model Performance -- 6.2 Zero Shot Prompting Vs Supervised Fine-Tuning -- 6.3 Effect of Chain of Thought Prompting -- 6.4 Error Analysis -- 7 Conclusion -- References -- Adversarial Text Purification: A Large Language Model Approach for Defense -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Large Language Models

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