Sfoglia per Serie
SemRevRec: a recommender system based on user reviews and linked data
2017 Vagliano, Iacopo; Monti, DIEGO MICHELE; Morisio, Maurizio
Synopsis of the MBSE, Lean and Smart Manufacturing in the product and process design for an assessment of the strategy “Industry 4.0”
2018 Brusa, Eugenio
Test Time Adaptation for Egocentric Vision
2023 Peirone, SIMONE ALBERTO; Planamente, Mirco; Caputo, Barbara; Averta, Giuseppe
Towards a holistic human perception system for close human-robot collaboration
2023 Terreran, M.; Barcellona, L.; Allegro, D.; Ghidoni, S.
Towards Vocally-Composed Personalization Rules in the IoT
2021 De Russis, Luigi; Monge Roffarello, Alberto; Borsarelli, Carlo
Triplet Losses-based Matrix Factorization for Robust Recommendations
2022 Giobergia, Flavio
User Emotion Detection via Taxonomy Management: An Innovative System
2020 Cuzzocrea, A.; Pilato, G.; Fadda, E.
Visualizing ratings in recommender system datasets
2019 Monti, DIEGO MICHELE; Rizzo, Giuseppe; Morisio, Maurizio
Citazione | Data di pubblicazione | Autori | File |
---|---|---|---|
SemRevRec: a recommender system based on user reviews and linked data / Vagliano, Iacopo; Monti, DIEGO MICHELE; Morisio, Maurizio. - ELETTRONICO. - Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (Poster-RecSys 2017):(2017). (Intervento presentato al convegno 11th ACM Conference on Recommender Systems tenutosi a Como (Italy) nel August 28, 2017). | 1-gen-2017 | MONTI, DIEGO MICHELEMORISIO, MAURIZIO + | recsys2017_poster10.pdf |
Synopsis of the MBSE, Lean and Smart Manufacturing in the product and process design for an assessment of the strategy “Industry 4.0” / Brusa, Eugenio. - ELETTRONICO. - CEUR-WS.org/Vol- 2248:(2018), pp. 21-30. (Intervento presentato al convegno CIISE 2018 - Conferenza INCOSE Italia su Systems Engineering tenutosi a ROMA nel 28-30 Novembre 2018). | 1-gen-2018 | BRUSA, Eugenio | Brusa_MBSE_LM_SM - Revv.pdf |
Test Time Adaptation for Egocentric Vision / Peirone, SIMONE ALBERTO; Planamente, Mirco; Caputo, Barbara; Averta, Giuseppe. - ELETTRONICO. - 3486:(2023), pp. 42-47. (Intervento presentato al convegno Ital-IA 2023 Thematic Workshops tenutosi a Pisa nel 29-30 Maggio 2023). | 1-gen-2023 | Simone Alberto PeironeMirco PlanamenteBarbara CaputoGiuseppe Averta | 159.pdf |
Towards a holistic human perception system for close human-robot collaboration / Terreran, M.; Barcellona, L.; Allegro, D.; Ghidoni, S.. - 3417:(2023), pp. 1-7. (Intervento presentato al convegno 9th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2022 tenutosi a Udine (ITA) nel November 30, 2022). | 1-gen-2023 | Barcellona L. + | short1.pdf |
Towards Vocally-Composed Personalization Rules in the IoT / De Russis, Luigi; Monge Roffarello, Alberto; Borsarelli, Carlo. - ELETTRONICO. - 3053:(2021), pp. 1-5. (Intervento presentato al convegno 2nd International Workshop on Empowering People in Dealing with Internet of Things Ecosystems (EMPATHY 2021) tenutosi a Bari (Italy) nel August 30, 2021). | 1-gen-2021 | De Russis, LuigiMonge Roffarello, Alberto + | vocal-eud.pdf; paper_1.pdf |
Triplet Losses-based Matrix Factorization for Robust Recommendations / Giobergia, Flavio. - 3318:(2022). (Intervento presentato al convegno CIKM 2022 Workshops tenutosi a Atlanta (USA) nel October 17-21, 2022). | 1-gen-2022 | Giobergia, Flavio | short11.pdf |
User Emotion Detection via Taxonomy Management: An Innovative System / Cuzzocrea, A.; Pilato, G.; Fadda, E.. - 2646:(2020), pp. 334-342. (Intervento presentato al convegno 28th Italian Symposium on Advanced Database Systems, SEBD 2020 tenutosi a Villasimius (Italy) nel 21th to 24th of June 2020). | 1-gen-2020 | Fadda E. + | 34-paper.pdf |
Visualizing ratings in recommender system datasets / Monti, DIEGO MICHELE; Rizzo, Giuseppe; Morisio, Maurizio. - ELETTRONICO. - 2450:(2019), pp. 60-64. (Intervento presentato al convegno 13th ACM Conference on Recommender Systems tenutosi a Copenhagen (DK) nel 16th-20th September 2019). | 1-gen-2019 | Diego MontiGiuseppe RizzoMaurizio Morisio | Visualizing_Ratings_in_Recommender_System_Datasets.pdf |
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