| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910151628003321 |
|
|
Titolo |
Children of the further dark [[electronic resource] ] : the poetry of Christopher Dewdney / / selected with an introduction by Karl E. Jirgens |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Waterloo, Ont., : Wilfrid Laurier University Press, c2007 |
|
|
|
|
|
|
|
ISBN |
|
1-55458-715-8 |
1-280-90802-5 |
9786610908028 |
1-55458-102-8 |
|
|
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
English poetry |
English literature |
Electronic books. |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Bibliographic Level Mode of Issuance: Monograph |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references. |
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNIORUON00262726 |
|
|
Titolo |
Duo |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
[Bruxelles], : Le Grand Miroir |
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Collezione |
|
|
|
|
|
3. |
Record Nr. |
UNINA9910992791503321 |
|
|
Autore |
Liu Fan |
|
|
Titolo |
Advancing Recommender Systems with Graph Convolutional Networks / / by Fan Liu, Liqiang Nie |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2025.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (166 pages) |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Information storage and retrieval systems |
Artificial intelligence |
Neural networks (Computer science) |
Information Storage and Retrieval |
Artificial Intelligence |
Mathematical Models of Cognitive Processes and Neural Networks |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Preface -- 1) Introduction -- 2) Interest-aware Message-Passing Graph Convolutional Network -- 3) Cluster-based Graph Collaborative Filtering -- 4) Semantic Aspect-aware Graph Convolutional Network -- 5) Attribute-aware Attentive Graph Convolutional Network -- 6) Light Graph Transformer Model -- 7) Research Frontiers. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book systematically examines scalability and effectiveness |
|
|
|
|
|
|
|
|
|
|
challenges related to the application of graph convolutional networks (GCNs) in recommender systems. By effectively modeling graph structures, GCNs excel in capturing high-order relationships between users and items, enabling the creation of enriched and expressive representations. The book focuses on two overarching problem categories: the first area deals with problems specific to GCN-based recommendation models, including over-smoothing, noisy neighboring nodes, and interpretability limitations. The second one encompasses broader challenges in recommendation systems that GCN-based methods are particularly well-suited to address as the attribute missing problem or feature misalignment. Through rigorous exploration of these challenges, this book presents innovative GCN-based solutions to push the boundaries of recommender system design. To this end, techniques such as interest-aware message-passing strategy, cluster-based collaborative filtering, semantic aspects extraction, attribute-aware attention mechanisms, and light graph transformer are presented. Each chapter combines theoretical insights with practical implementations and experimental validation, offering a comprehensive resource for researchers, advanced professionals, and graduate students alike. |
|
|
|
|
|
| |