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Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part IX

  • Conference proceedings
  • © 2024

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Overview

Editors:
  1. Albert Bifet

    1. LTCI, Télécom Paris, Palaiseau Cedex, France

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  2. Tomas Krilavičius

    1. Faculty of Informatics, Vytautas Magnus University, Akademija, Lithuania

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  3. Ioanna Miliou

    1. Stockholm University, Kista, Sweden

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  4. Slawomir Nowaczyk

    1. School of Information Technology, Halmstad University, Halmstad, Sweden

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14949)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ECML PKDD 2024.

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About this book

This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024.

 

The papers presented in these proceedings are from the following three conference tracks: -

Research Track: The 202 full papers presented here, from this track, were carefully reviewed and selected from 826 submissions. These papers are present in the following volumes: Part I, II, III, IV, V, VI, VII, VIII.

 

Demo Track: The 14 papers presented here, from this track, were selected from 30 submissions. These papers are present in the following volume: Part VIII.

 

Applied Data Science Track: The 56 full papers presented here, from this track, were carefully reviewed and selected from 224 submissions. These papers are present in the following volumes: Part IX and Part X.

Keywords

Table of contents (28 papers)

  1. Front Matter

    Pages i-lvii
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  2. Applied Data Science Track

    1. Front Matter

      Pages 1-1
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    2. VulEXplaineR: XAI for Vulnerability Detection on Assembly Code

      • Samaneh Mahdavifar, Mohd Saqib, Benjamin C. M. Fung, Philippe Charland, Andrew Walenstein
      Pages 3-20
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    3. Guiding Catalogue Enrichment with User Queries

      • Yupei Du, Jacek Golebiowski, Philipp Schmidt, Ziawasch Abedjan
      Pages 21-37
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    4. PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning

      • Frederico Metelo, Cláudia Soares, Stevo Racković, Pedro Ákos Costa
      Pages 38-54
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    5. Robust Interaction-Based Relevance Modeling for Online e-Commerce Search

      • Ben Chen, Huangyu Dai, Xiang Ma, Wen Jiang, Wei Ning
      Pages 55-71
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    6. Learning Optimal Linear Precoding for Cell-Free Massive MIMO with GNN

      • Benjamin Parlier, Lou Salaün, Hong Yang
      Pages 72-88
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    7. Multiple Hypergraph Learning for Ephemeral Group Recommendation

      • Rui Zhao, Beihong Jin, Yimin Lv, Yiyuan Zheng, Weijiang Lai
      Pages 89-105
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    8. Spoofing Transaction Detection with Group Perceptual Enhanced Graph Neural Network

      • Le Kang, Tai-Jiang Mu, XiaoDong Ning
      Pages 106-122
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    9. Self-SLAM: A Self-supervised Learning Based Annotation Method to Reduce Labeling Overhead

      • Alfiya M. Shaikh, Hrithik Nambiar, Kshitish Ghate, Swarnali Banik, Sougata Sen, Surjya Ghosh et al.
      Pages 123-140
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    10. Multi-intent Driven Contrastive Sequential Recommendation

      • Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao, Weijiang Lai, Tao Xiang
      Pages 141-156
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    11. KAT5: Knowledge-Aware Transfer Learning with a Text-to-Text Transfer Transformer

      • Mohammad Golam Sohrab, Makoto Miwa
      Pages 157-173
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    12. Asymmetric Graph-Based Deep Reinforcement Learning for Portfolio Optimization

      • Haoyu Sun, Xin Liu, Yuxuan Bian, Peng Zhu, Dawei Cheng, Yuqi Liang
      Pages 174-189
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    13. Code Summarization with Project-Specific Features

      • Yu Wang, Xin Liu, Xuesong Lu, Aoying Zhou
      Pages 190-206
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    14. Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-Regenerative Life Support System Telemetry

      • Ferdinand Rewicki, Jakob Gawlikowski, Julia Niebling, Joachim Denzler
      Pages 207-222
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    15. Long-Term Fairness in Ride-Hailing Platform

      • Yufan Kang, Jeffrey Chan, Wei Shao, Flora D. Salim, Christopher Leckie
      Pages 223-239
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    16. A Merge Sort Based Ranking System for the Evaluation of Large Language Models

      • Chenchen Li, Linfeng Shi, Chunyi Zhou, Zhaoxin Huan, Chengfu Tang, Xiaolu Zhang et al.
      Pages 240-255
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    17. Enhancing HVAC Control Efficiency: A Hybrid Approach Using Imitation and Reinforcement Learning

      • Kevlyn Kadamala, Des Chambers, Enda Barrett
      Pages 256-270
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    18. Synthesis of Standard 12-Lead ECG from Single-Lead ECG Using Shifted Diffusion Models

      • Jingwei Liu, Hongyan Li, Shenda Hong
      Pages 271-286
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    19. SAGS-DynamicBio: Integrating Semantic-Aware and Graph Structure-Aware Embedding for Dynamic Biological Data with Knowledge Graphs

      • Yao Liu, Yongfei Zhang, Xin Wang
      Pages 287-302
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Other volumes

  1. Machine Learning and Knowledge Discovery in Databases. Research Track

  2. Machine Learning and Knowledge Discovery in Databases. Research Track

  3. Machine Learning and Knowledge Discovery in Databases. Research Track

  4. Machine Learning and Knowledge Discovery in Databases. Research Track

  5. Machine Learning and Knowledge Discovery in Databases. Research Track

  6. Machine Learning and Knowledge Discovery in Databases. Research Track

  7. Machine Learning and Knowledge Discovery in Databases. Research Track

  8. Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track

  9. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

  10. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

Editors and Affiliations

  • LTCI, Télécom Paris, Palaiseau Cedex, France

    Albert Bifet

  • Faculty of Informatics, Vytautas Magnus University, Akademija, Lithuania

    Tomas Krilavičius

  • Stockholm University, Kista, Sweden

    Ioanna Miliou

  • School of Information Technology, Halmstad University, Halmstad, Sweden

    Slawomir Nowaczyk

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