Advances on Graph-Based Approaches in Information Retrieval (eBook, PDF)

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

• Format: PDF

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 89
• Erscheinungstermin: 9. Oktober 2024
• Englisch
• ISBN-13: 9783031713828
• Artikelnr.: 72242927

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.