Advances on Graph-Based Approaches in Information Retrieval: First International Workshop, IRonGraphs 2024, Glasgow, UK, March 24, 2024, Proceedings
Author:   Ludovico Boratto ,  Daniele Malitesta ,  Mirko Marras ,  Giacomo Medda
Publisher:   Springer International Publishing AG
Edition:   2025 ed.
Volume:   2197
ISBN:  

9783031713811


Pages:   89
Publication Date:   10 October 2024
Format:   Paperback
Availability:   Not yet available   Availability explained
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Advances on Graph-Based Approaches in Information Retrieval: First International Workshop, IRonGraphs 2024, Glasgow, UK, March 24, 2024, Proceedings


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Overview

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.

Full Product Details

Author:   Ludovico Boratto ,  Daniele Malitesta ,  Mirko Marras ,  Giacomo Medda
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2025 ed.
Volume:   2197
ISBN:  

9783031713811


ISBN 10:   3031713818
Pages:   89
Publication Date:   10 October 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

.-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.

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