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Record Nr. |
UNINA9910983342003321 |
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Titolo |
Advances on Graph-Based Approaches in Information Retrieval : First International Workshop, IRonGraphs 2024, Glasgow, UK, March 24, 2024, Proceedings / / edited by Ludovico Boratto, Daniele Malitesta, Mirko Marras, Giacomo Medda, Cataldo Musto, Erasmo Purificato |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (98 pages) |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 2197 |
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Disciplina |
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Soggetti |
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Natural language processing (Computer science) |
Machine learning |
Information storage and retrieval systems |
Database management |
Data mining |
Natural Language Processing (NLP) |
Machine Learning |
Information Storage and Retrieval |
Database Management System |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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.-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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Sommario/riassunto |
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This book constitutes the refereed proceedings of the First |
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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. |
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