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ORCIDYashar Deldjoo
- > Home > Persons > Yashar Deldjoo
Publications
- 2021
[j12]Yashar Deldjoo
, Markus Schedl, Paolo Cremonesi, Gabriella Pasi:
Recommender Systems Leveraging Multimedia Content. ACM Comput. Surv. 53(5): 106:1-106:38 (2021)- 2019
- [j6]Yashar Deldjoo, Maurizio Ferrari Dacrema, Mihai Gabriel Constantin, Hamid Eghbal-zadeh, Stefano Cereda, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi:
Movie genome: alleviating new item cold start in movie recommendation. User Model. User Adapt. Interact. 29(2): 291-343 (2019) - [c19]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. IntRS@RecSys 2019: 72-76 - [i4]Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi:
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features. CoRR abs/1908.11055 (2019) - 2018
- [j4]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi:
Using visual features based on MPEG-7 and deep learning for movie recommendation. Int. J. Multim. Inf. Retr. 7(4): 207-219 (2018) - [c15]Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi:
Content-Based Multimedia Recommendation Systems: Definition and Application Domains. IIR 2018 - [c12]Yashar Deldjoo, Mihai Gabriel Constantin, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
MMTF-14K: a multifaceted movie trailer feature dataset for recommendation and retrieval. MMSys 2018: 450-455 - [c11]Yashar Deldjoo, Mihai Gabriel Constantin, Hamid Eghbal-Zadeh, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi:
Audio-visual encoding of multimedia content for enhancing movie recommendations. RecSys 2018: 455-459 - 2017
- [c9]Yashar Deldjoo, Paolo Cremonesi, Markus Schedl, Massimo Quadrana:
The effect of different video summarization models on the quality of video recommendation based on low-level visual features. CBMI 2017: 20:1-20:6 - [c8]Yashar Deldjoo, Cristina Frà, Massimo Valla, Paolo Cremonesi:
Letting Users Assist What to Watch: An Interactive Query-by-Example Movie Recommendation System. IIR 2017: 63-66 - [c7]Mehdi Elahi, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Leonardo Cella, Stefano Cereda, Paolo Cremonesi:
Exploring the Semantic Gap for Movie Recommendations. RecSys 2017: 326-330 - [i3]Yashar Deldjoo, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi:
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation. CoRR abs/1704.06109 (2017) - 2016
- [j2]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla, Massimo Quadrana:
Content-Based Video Recommendation System Based on Stylistic Visual Features. J. Data Semant. 5(2): 99-113 (2016) - [c5]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla:
Recommending Movies Based on Mise-en-Scene Design. CHI Extended Abstracts 2016: 1540-1547 - [c4]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Farshad Bakhshandegan Moghaddam, Andrea Luigi Edoardo Caielli:
How to Combine Visual Features with Tags to Improve Movie Recommendation Accuracy? EC-Web 2016: 34-45 - [c3]Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi:
Using Visual Features and Latent Factors for Movie Recommendation. CBRecSys@RecSys 2016: 15-18 - [i1]Yashar Deldjoo, Shengping Zhang, Bahman Zanj, Paolo Cremonesi, Matteo Matteucci:
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking? CoRR abs/1608.00168 (2016) - 2015
- [c2]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi, Franca Garzotto:
Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles. CHItaly 2015: 162-165 - [c1]Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi:
Toward Building a Content-Based Video Recommendation System Based on Low-Level Features. EC-Web 2015: 45-56
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