Advances on Graph-Based Approaches in Information Retrieval

First International Workshop, IRonGraphs 2024, Glasgow, UK, March 24, 2024, Proceedings
Herausgegeben:Boratto, Ludovico; Malitesta, Daniele; Marras, Mirko; Medda, Giacomo; Musto, Cataldo; Purificato, Erasmo

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the First International Workshop on Graph-Based Approaches in Information Retrieval, IRonGraphs 2024, held in Glasgow, UK, on March 24, 2024.

The 6 full papers included in this book were carefully reviewed and selected from 14 submissions. They focus on diverse novel contributions, with presentations on knowledge-aware graph-based recommender systems using user-based semantic features filtering, source-target node distance impacts on adversarial attacks in social network recommendations.

Produktdetails

• Communications in Computer and Information Science 2197
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-71381-1
• 2025
• Seitenzahl: 100
• Erscheinungstermin: 10. Oktober 2024
• Englisch
• Abmessung: 235mm x 155mm x 6mm
• Gewicht: 166g
• ISBN-13: 9783031713811
• ISBN-10: 3031713818
• Artikelnr.: 71319742

Inhaltsangabe

.-Soccer-GraphRAG: Applications of GraphRAG in Soccer.
.- Enhanced Semantic Understanding with Graph-based Information Retrieval.
.- Identifying Shopping Intent in Product QA for Proactive Recommendations.
.- KGUF: Simple Knowledge-aware Graph-based Recommender with User-based Semantic Features Filtering.
.- The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval.
.- The Impact of Source-Target Node Distance on Vicious Adversarial Attacks in Social Network Recommendation Systems.