Advances in Knowledge Discovery and Data Mining : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng.

Format:

Book

Contributor:

Kashima, Hisashi, editor.

Ide, Tsuyoshi, editor.

Peng, Wen-Chih, editor.

Series:

Lecture Notes in Artificial Intelligence, 2945-9141 ; 13937

Language:

English

Subjects (All):

Artificial intelligence.

Algorithms.

Education--Data processing.

Education.

Computer science--Mathematics.

Computer science.

Computer vision.

Computer engineering.

Computer networks.

Artificial Intelligence.

Design and Analysis of Algorithms.

Computers and Education.

Mathematics of Computing.

Computer Vision.

Computer Engineering and Networks.

Local Subjects:

Artificial Intelligence.

Design and Analysis of Algorithms.

Computers and Education.

Mathematics of Computing.

Computer Vision.

Computer Engineering and Networks.

Physical Description:

1 online resource (419 pages)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2023.

Summary:

The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023. The 143 papers presented in these proceedings were carefully reviewed and selected from 813 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.

Contents:

Big data

Toward Explainable Recommendation Via Counterfactual Reasoning

Online Volume Optimization for Notifications via Long Short-Term Value Modeling

Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases

Financial data

Joint Latent Topic Discovery and Expectation Modeling for Financial Markets

Let the model make financial senses: a Text2Text generative approach for financial complaint identification

Information retrieval and search

Web-scale Semantic Product Search With Large Language Models

Multi-task learning based Keywords weighted Siamese Model for semantic retrieval

Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion

MFBE: Leveraging Multi-Field Information of FAQs for Efficient Dense Retrieval

Isotropic Representation Can Improve Dense Retrieval

Knowledge-Enhanced Prototypical Network with Structural Semantics forFew-Shot Relation Classification

Internet of Things

MIDFA : Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection

Medical and biological data

Vision Transformers for Small Histological Datasets learned through Knowledge Distillation

Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis

DKFM: Dual Knowledge-guided Fusion Model for Drug Recommendation

Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge

Multimedia and multimodal data

An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance

Dynamically-Scaled Deep Canonical Correlation Analysis

TCR: Short Video Title Generation and Cover Selection with Attention Refinement

ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval

Recommender systems

Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations

Interest Driven Graph Structure Learning for Session-Based Recommendation

Multi-behavior Guided Temporal Graph Attention Network for Recommendation

Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation

Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities

Global-Aware External Attention Deep Model for Sequential Recommendation

Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking

Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation

kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval

Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation

RLMixer: A Reinforcement Learning Approach For Integrated Ranking With Contrastive User Preference Modeling.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Kashima, Hisashi Advances in Knowledge Discovery and Data Mining

ISBN:

9783031333804

3031333802

OCLC:

1380721799