Advances on Graph-Based Approaches in Information Retrieval Advances on Graph-Based Approaches in Information Retrieval

Advances on Graph-Based Approaches in Information Retrieval

First International Workshop, IRonGraphs 2024, Glasgow, UK, March 24, 2024, Proceedings

Ludovico Boratto và các tác giả khác
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Lời Giới Thiệu Của Nhà Xuất Bản

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.

THỂ LOẠI
Máy Vi Tính & Internet
ĐÃ PHÁT HÀNH
2024
9 tháng 10
NGÔN NGỮ
EN
Tiếng Anh
ĐỘ DÀI
98
Trang
NHÀ XUẤT BẢN
Springer Nature Switzerland
NGƯỜI BÁN
Springer Nature B.V.
KÍCH THƯỚC
11,3
Mb

Sách Khác Của Ludovico Boratto, Daniele Malitesta, Mirko Marras, Giacomo Medda, Cataldo Musto & Erasmo Purificato

Recommender Systems for Sustainability and Social Good Recommender Systems for Sustainability and Social Good
Recommender Systems for Sustainability and Social Good
2025
Advances in Bias and Fairness in Information Retrieval Advances in Bias and Fairness in Information Retrieval
Advances in Bias and Fairness in Information Retrieval
2024
Group Recommender Systems Group Recommender Systems
Group Recommender Systems
2023
Advances in Bias and Fairness in Information Retrieval Advances in Bias and Fairness in Information Retrieval
Advances in Bias and Fairness in Information Retrieval
2023
Advances in Bias and Fairness in Information Retrieval Advances in Bias and Fairness in Information Retrieval
Advances in Bias and Fairness in Information Retrieval
2022
Bias and Social Aspects in Search and Recommendation Bias and Social Aspects in Search and Recommendation
Bias and Social Aspects in Search and Recommendation
2020