Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Alessandro Suglia"'
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdefc59f69bce8e10508b3342b6c6f70
https://doi.org/10.18653/v1/2022.acl-srw.11
https://doi.org/10.18653/v1/2022.acl-srw.11
Publikováno v:
Information Systems. 86:1-8
Recently, several methods have been proposed for introducing Linked Open Data (LOD) into recommender systems. LOD can be used to enrich the representation of items by leveraging RDF statements and adopting graph-based methods to implement effective r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::708b4e342010f7614435ff880005c417
https://doi.org/10.1016/j.is.2019.07.001
https://doi.org/10.1016/j.is.2019.07.001
Publikováno v:
Intelligenza Artificiale. 12:125-141
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c276381828ac246db180fc81ddd0d262
https://doi.org/10.3233/ia-170031
https://doi.org/10.3233/ia-170031
Publikováno v:
SIGIR
Perceptual Speed (PS) is a cognitive ability that is known to affect multiple factors in Information Retrieval (IR) such as a user's search performance and subjective experience. However PS tests are difficult to administer which limits the design of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b35a8403e0211c193af0a07255cb7c1c
https://doi.org/10.1145/3397271.3401210
https://doi.org/10.1145/3397271.3401210
Autor:
Oliver Lemon, Ioannis Konstas, Andrea Vanzo, Desmond Elliott, Alessandro Suglia, Stella Frank, Emanuele Bastianelli
Publikováno v:
ACL
Suglia, A, Konstas, I, Vanzo, A, Bastianelli, E, Elliott, D, Frank, S & Lemon, O 2020, CompGuessWhat?! A Multi-task Evaluation Framework for Grounded Language Learning . in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics, pp. 7625–7641, 58th Annual Meeting of the Association for Computational Linguistics, Online, 05/07/2020 . https://doi.org/10.18653/v1/2020.acl-main.682
Suglia, A, Konstas, I, Vanzo, A, Bastianelli, E, Elliott, D, Frank, S & Lemon, O 2020, CompGuessWhat?! A Multi-task Evaluation Framework for Grounded Language Learning . in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics, pp. 7625–7641, 58th Annual Meeting of the Association for Computational Linguistics, Online, 05/07/2020 . https://doi.org/10.18653/v1/2020.acl-main.682
Approaches to Grounded Language Learning typically focus on a single task-based final performance measure that may not depend on desirable properties of the learned hidden representations, such as their ability to predict salient attributes or to gen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4498afdf92b23e3e5ada3777eda39559
https://doi.org/10.18653/v1/2020.acl-main.682
https://doi.org/10.18653/v1/2020.acl-main.682
Autor:
Pasquale Lops, Claudio Greco, Giovanni Semeraro, Alessandro Suglia, Marco de Gemmis, Cataldo Musto
Publikováno v:
UMAP
In this paper we investigate the effectiveness of Recurrent Neural Networks (RNNs) in a top-N content-based recommendation scenario. Specifically, we propose a deep architecture which adopts Long Short Term Memory (LSTM) networks to jointly learn two
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29e8b10ac5b41179f5c3915c584db757
https://doi.org/10.1145/3079628.3079684
https://doi.org/10.1145/3079628.3079684
Publikováno v:
AI*IA 2017 Advances in Artificial Intelligence ISBN: 9783319701684
AI*IA
AI*IA
Sentence-based extractive summarization aims at automatically generating shorter versions of texts by extracting from them the minimal set of sentences that are necessary and sufficient to cover their content. Providing effective solutions to this ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73ef6a10f37aadb28891f1849d9ce40f
https://doi.org/10.1007/978-3-319-70169-1_7
https://doi.org/10.1007/978-3-319-70169-1_7
Publikováno v:
AI*IA 2017 Advances in Artificial Intelligence ISBN: 9783319701684
AI*IA
AI*IA
In this paper, we propose a framework based on Hierarchical Reinforcement Learning for dialogue management in a Conversational Recommender System scenario. The framework splits the dialogue into more manageable tasks whose achievement corresponds to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aaeefc254ce0eb78113b2d27d34c643
https://doi.org/10.1007/978-3-319-70169-1_28
https://doi.org/10.1007/978-3-319-70169-1_28
Autor:
Amanda Cercas Curry, Ioannis Papaioannou, Alessandro Suglia, Shubham Agarwal, Igor Shalyminov, Xu Xinnuo, Ondrej Dusek, Arash Eshghi, Ioannis Konstas, Verena Rieser, Oliver Lemon
Publikováno v:
Heriot-Watt University
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::13ae1efdc33db8f25e24d1bbf6bd5492
https://researchportal.hw.ac.uk/en/publications/88ed6d57-efa0-4a2b-9456-f1a25cde25e5
https://researchportal.hw.ac.uk/en/publications/88ed6d57-efa0-4a2b-9456-f1a25cde25e5
Publikováno v:
Heriot-Watt University
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::af09fdfe0fffc95fd4a1095ffb78761a
https://researchportal.hw.ac.uk/en/publications/7e7968cb-f064-44a5-bff0-424b28958d3e
https://researchportal.hw.ac.uk/en/publications/7e7968cb-f064-44a5-bff0-424b28958d3e