default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYashar Deldjoo
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j24]Yashar Deldjoo
, Markus Schedl, Peter Knees:
Content-driven music recommendation: Evolution, state of the art, and challenges. Comput. Sci. Rev. 51: 100618 (2024)- [j23]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. ACM Comput. Surv. 56(4): 87:1-87:37 (2024) - [j22]Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci:
Interactive Question Answering Systems: Literature Review. ACM Comput. Surv. 56(9): 239:1-239:38 (2024) - [j21]Ali Tourani, Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo:
CAPRI: Context-aware point-of-interest recommendation framework. Softw. Impacts 19: 100606 (2024) - [j20]Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo:
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems. Trans. Recomm. Syst. 2(3): 19:1-19:24 (2024) - [j19]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
Fairness in recommender systems: research landscape and future directions. User Model. User Adapt. Interact. 34(1): 59-108 (2024) - [c61]Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano:
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). KDD 2024: 6448-6458 - [c60]Yashar Deldjoo, Julian J. McAuley, Scott Sanner, Pablo Castells, Shuai Zhang, Enrico Palumbo:
The 1st International Workshop on Risks, Opportunities, and Evaluation of Generative Models in Recommendation (ROEGEN). RecSys 2024: 1250-1252 - [i38]Yashar Deldjoo:
Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recency. CoRR abs/2401.10545 (2024) - [i37]Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo:
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems. CoRR abs/2402.00485 (2024) - [i36]Yashar Deldjoo, Tommaso Di Noia:
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System. CoRR abs/2403.05668 (2024) - [i35]Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano:
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). CoRR abs/2404.00579 (2024) - [i34]Lemei Zhang, Peng Liu, Yashar Deldjoo, Yong Zheng, Jon Atle Gulla:
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open Challenges. CoRR abs/2404.03788 (2024) - [i33]Yashar Deldjoo:
FairEvalLLM. A Comprehensive Framework for Benchmarking Fairness in Large Language Model Recommender Systems. CoRR abs/2405.02219 (2024) - [i32]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio:
XAI4LLM. Let Machine Learning Models and LLMs Collaborate for Enhanced In-Context Learning in Healthcare. CoRR abs/2405.06270 (2024) - [i31]Leila Tavakoli, Giovanni Castiglia, Federica Calò, Yashar Deldjoo, Hamed Zamani, Johanne R. Trippas:
Understanding Modality Preferences in Search Clarification. CoRR abs/2406.19546 (2024) - [i30]Anton Korikov, Scott Sanner, Yashar Deldjoo, Zhankui He, Julian J. McAuley, Arnau Ramisa, René Vidal, Mahesh Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano, Francesco Ricci:
Large Language Model Driven Recommendation. CoRR abs/2408.10946 (2024) - [i29]Arnau Ramisa, René Vidal, Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Mahesh Sathiamoorthy, Atoosa Kasrizadeh, Silvia Milano, Francesco Ricci:
Multi-modal Generative Models in Recommendation System. CoRR abs/2409.10993 (2024) - [i28]Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasrizadeh, Silvia Milano, Francesco Ricci:
Recommendation with Generative Models. CoRR abs/2409.15173 (2024) - 2023
- [j18]Enrique Amigó, Yashar Deldjoo, Stefano Mizzaro, Alejandro Bellogín:
A unifying and general account of fairness measurement in recommender systems. Inf. Process. Manag. 60(1): 103115 (2023) - [c59]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia:
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPT. ECAI Workshops (1) 2023: 382-397 - [c58]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo:
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering. ECIR (1) 2023: 33-48 - [c57]Dario Di Palma, Vito Walter Anelli, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo, Yashar Deldjoo, Tommaso Di Noia:
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective. IIR 2023: 79-84 - [c56]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Carmelo Ardito, Eugenio Di Sciascio:
Smart Electrical Grids Under the Lens of Adversarial Attacks. Ital-IA 2023: 616-621 - [c55]Marta Moscati, Yashar Deldjoo, Giulio Davide Carparelli, Markus Schedl:
Multiobjective Hyperparameter Optimization of Recommender Systems. Perspectives@RecSys 2023 - [c54]Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Computational Versus Perceived Popularity Miscalibration in Recommender Systems. SIGIR 2023: 1889-1893 - [i27]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary, Giovanni Servedio:
Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids. CoRR abs/2303.18136 (2023) - [i26]Ali Tourani, Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo:
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework. CoRR abs/2306.11395 (2023) - [i25]Yashar Deldjoo:
Fairness of ChatGPT and the Role Of Explainable-Guided Prompts. CoRR abs/2307.11761 (2023) - [i24]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia:
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPT. CoRR abs/2308.09731 (2023) - [i23]Giovanni Pellegrini, Vittorio Maria Faraco, Yashar Deldjoo:
Fairness for All: Investigating Harms to Within-Group Individuals in Producer Fairness Re-ranking Optimization - A Reproducibility Study. CoRR abs/2309.09277 (2023) - 2022
- [j17]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks. ACM Comput. Surv. 54(2): 35:1-35:38 (2022) - [j16]Hossein A. Rahmani, Yashar Deldjoo, Tommaso Di Noia:
The role of context fusion on accuracy, beyond-accuracy, and fairness of point-of-interest recommendation systems. Expert Syst. Appl. 205: 117700 (2022) - [j15]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary:
Visual inspection of fault type and zone prediction in electrical grids using interpretable spectrogram-based CNN modeling. Expert Syst. Appl. 210: 118368 (2022) - [j14]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
User-controlled federated matrix factorization for recommender systems. J. Intell. Inf. Syst. 58(2): 287-309 (2022) - [j13]Mohammadmehdi Naghiaei, Hossein A. Rahmani, Yashar Deldjoo:
PyCPFair: A framework for consumer and producer fairness in recommender systems. Softw. Impacts 13: 100382 (2022) - [c53]Hossein A. Rahmani, Yashar Deldjoo, Ali Tourani, Mohammadmehdi Naghiaei:
The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation. BIAS 2022: 56-68 - [c52]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo:
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews. DL4SR@CIKM 2022 - [c51]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary:
IEEE13-AdvAttack A Novel Dataset for Benchmarking the Power of Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grid. CIKM 2022: 3817-3821 - [c50]Marta Moscati, Emilia Parada-Cabaleiro, Yashar Deldjoo, Eva Zangerle, Markus Schedl:
Music4All-Onion - A Large-Scale Multi-faceted Content-Centric Music Recommendation Dataset. CIKM 2022: 4339-4343 - [c49]Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Felice Antonio Merra:
Leveraging Content-Style Item Representation for Visual Recommendation. ECIR (2) 2022: 84-92 - [c48]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo:
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering. MORS@RecSys 2022 - [c47]Giovanni Castiglia, Ayoub El Majjodi, Federica Calò, Yashar Deldjoo, Fedelucio Narducci, Alain Starke, Christoph Trattner:
Nudging Towards Health in a Conversational Food Recommender System Using Multi-Modal Interactions and Nutrition Labels. KaRS@RecSys 2022: 29-35 - [c46]Hossein A. Rahmani, Mohammadmehdi Naghiaei, Ali Tourani, Yashar Deldjoo:
Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation. RecSys 2022: 598-603 - [c45]Mohammadmehdi Naghiaei, Hossein A. Rahmani, Yashar Deldjoo:
CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems. SIGIR 2022: 770-779 - [r2]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Adversarial Recommender Systems: Attack, Defense, and Advances. Recommender Systems Handbook 2022: 335-379 - [r1]Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He:
Multimedia Recommender Systems: Algorithms and Challenges. Recommender Systems Handbook 2022: 973-1014 - [d1]Marta Moscati, Emilia Parada-Cabaleiro, Yashar Deldjoo, Eva Zangerle, Markus Schedl:
Music4All-Onion. Zenodo, 2022
- [i22]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. CoRR abs/2202.02757 (2022) - [i21]Hossein A. Rahmani, Yashar Deldjoo, Ali Tourani, Mohammadmehdi Naghiaei:
The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation. CoRR abs/2202.13307 (2022) - [i20]Mohammadmehdi Naghiaei, Hossein A. Rahmani, Yashar Deldjoo:
CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems. CoRR abs/2204.08085 (2022) - [i19]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
A Survey of Research on Fair Recommender Systems. CoRR abs/2205.11127 (2022) - [i18]Hossein A. Rahmani, Mohammadmehdi Naghiaei, Ali Tourani, Yashar Deldjoo:
Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation. CoRR abs/2207.11609 (2022) - [i17]Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci:
Interactive Question Answering Systems: Literature Review. CoRR abs/2209.01621 (2022) - 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) - [j11]Yashar Deldjoo, Alejandro Bellogín, Tommaso Di Noia:
Explaining recommender systems fairness and accuracy through the lens of data characteristics. Inf. Process. Manag. 58(5): 102662 (2021) - [j10]Jens Adamczak, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Peter Knees, Gerard Paul Leyson, Philipp Monreal:
Session-based Hotel Recommendations Dataset: As part of the ACM Recommender System Challenge 2019. ACM Trans. Intell. Syst. Technol. 12(1): 1:1-1:20 (2021) - [j9]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín, Tommaso Di Noia:
A flexible framework for evaluating user and item fairness in recommender systems. User Model. User Adapt. Interact. 31(3): 457-511 (2021) - [c44]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
A Formal Analysis of Recommendation Quality of Adversarially-trained Recommenders. CIKM 2021: 2852-2856 - [c43]Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Felice Antonio Merra:
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems. CVPR Workshops 2021: 3961-3967 - [c42]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
FedeRank: User Controlled Feedback with Federated Recommender Systems. ECIR (1) 2021: 32-47 - [c41]Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. FLAIRS 2021 - [c40]Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Felice Antonio Merra:
A Regression Framework to Interpret the Robustness of Recommender Systems Against Shilling Attacks. IIR 2021 - [c39]Carmelo Ardito, Yashar Deldjoo, Eugenio Di Sciascio, Fatemeh Nazary, Gianluca Sapienza:
ISCADA: Towards a Framework for Interpretable Fault Prediction in Smart Electrical Grids. INTERACT (5) 2021: 270-274 - [c38]Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Gaetano Pernisco, Vito Renò, Ettore Stella:
Towards Improving Car Point-Cloud Tracking Via Detection Updates. IPMV 2021: 30-34 - [c37]Carmelo Ardito, Yashar Deldjoo, Eugenio Di Sciascio, Fatemeh Nazary:
Revisiting Security Threat on Smart Grids: Accurate and Interpretable Fault Location Prediction and Type Classification. ITASEC 2021: 523-533 - [c36]Vito Walter Anelli, Luca Belli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci, Claudio Pomo:
Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications. RecSys 2021: 838-841 - [c35]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
How to put users in control of their data in federated top-N recommendation with learning to rank. SAC 2021: 1359-1362 - [c34]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
Federated Recommender Systems with Learning to Rank. SEBD 2021: 71-82 - [c33]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Felice Antonio Merra:
A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. SIGIR 2021: 1094-1103 - [c32]Yashar Deldjoo, Johanne R. Trippas, Hamed Zamani:
Towards Multi-Modal Conversational Information Seeking. SIGIR 2021: 1577-1587 - [i16]Yashar Deldjoo, Markus Schedl, Peter Knees:
Content-driven Music Recommendation: Evolution, State of the Art, and Challenges. CoRR abs/2107.11803 (2021) - [i15]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality. CoRR abs/2107.13876 (2021) - [i14]Alejandro Bellogín, Yashar Deldjoo:
Simulations for novel problems in recommendation: analyzing misinformation and data characteristics. CoRR abs/2110.04037 (2021) - 2020
- [j8]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara:
Prioritized multi-criteria federated learning. Intelligenza Artificiale 14(2): 183-200 (2020) - [c31]Carmelo Ardito, Yashar Deldjoo, Eugenio Di Sciascio, Fatemeh Nazary:
Interacting with Features: Visual Inspection of Black-box Fault Type Classification Systems in Electrical Grids. XAI.it@AI*IA 2020: 135-141 - [c30]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta:
Deep Learning-Based Adaptive Image Compression System for a Real-World Scenario. EAIS 2020: 1-8 - [c29]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Felice Antonio Merra:
SAShA: Semantic-Aware Shilling Attacks on Recommender Systems Exploiting Knowledge Graphs. ESWC 2020: 307-323 - [c28]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Adversarial Learning for Recommendation: Applications for Security and Generative Tasks - Concept to Code. RecSys 2020: 738-741 - [c27]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra, Giuseppe Acciani, Eugenio Di Sciascio:
Knowledge-enhanced Shilling Attacks for Recommendation. SEBD 2020: 310-317 - [c26]Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Felice Antonio Merra:
How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models. SIGIR 2020: 951-960 - [c25]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Adversarial Machine Learning in Recommender Systems (AML-RecSys). WSDM 2020: 869-872 - [i13]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Adversarial Machine Learning in Recommender Systems: State of the art and Challenges. CoRR abs/2005.10322 (2020) - [i12]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara:
Prioritized Multi-Criteria Federated Learning. CoRR abs/2007.08893 (2020) - [i11]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
How to Put Users in Control of their Data via Federated Pair-Wise Recommendation. CoRR abs/2008.07192 (2020) - [i10]Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. CoRR abs/2010.01329 (2020) - [i9]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
FedeRank: User Controlled Feedback with Federated Recommender Systems. CoRR abs/2012.11328 (2020)
2010 – 2019
- 2019
- [j7]Vahid Jalili, Matteo Matteucci, Jeremy Goecks, Yashar Deldjoo, Stefano Ceri:
Next Generation Indexing for Genomic Intervals. IEEE Trans. Knowl. Data Eng. 31(10): 2008-2021 (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) - [c24]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara:
Towards Effective Device-Aware Federated Learning. AI*IA 2019: 477-491 - [c23]Yashar Deldjoo, Markus Schedl:
Retrieving Relevant and Diverse Movie Clips Using the MFVCD-7K Multifaceted Video Clip Dataset. CBMI 2019: 1-4 - [c22]Yashar Deldjoo, Markus Schedl, Mehdi Elahi:
Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content. CBMI 2019: 1-4 - [c21]Yashar Deldjoo, Benny Kille, Markus Schedl, Andreas Lommatzsch, Jialie Shen:
The 2019 Multimedia for Recommender System Task: MovieREC and NewsREEL at MediaEval. MediaEval 2019 - [c20]Hossein A. Rahmani, Yashar Deldjoo, Markus Schedl:
A Regression Approach to Movie Rating Prediction Using Multimedia Content and Metadata. MediaEval 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 - [c18]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín Kouki, Tommaso Di Noia:
Recommender Systems Fairness Evaluation via Generalized Cross Entropy. RMSE@RecSys 2019 - [c17]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Assessing the Impact of a User-Item Collaborative Attack on Class of Users. ImpactRS@RecSys 2019 - [c16]Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Jens Adamczak, Gerard Paul Leyson, Philipp Monreal:
RecSys challenge 2019: session-based hotel recommendations. RecSys 2019: 570-571 - [e1]Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Jens Adamczak, Gerard Paul Leyson, Philipp Monreal:
Proceedings of the Workshop on ACM Recommender Systems Challenge, Copenhagen, Denmark, September 2019. ACM 2019, ISBN 978-1-4503-7667-9 [contents] - [i8]Jens Adamczak, Gerard Paul Leyson, Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Julia Neidhardt, Wolfgang Wörndl, Philipp Monreal:
Session-Based Hotel Recommendations: Challenges and Future Directions. CoRR abs/1908.00071 (2019) - [i7]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín, Tommaso Di Noia:
Recommender Systems Fairness Evaluation via Generalized Cross Entropy. CoRR abs/1908.06708 (2019) - [i6]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara:
Towards Effective Device-Aware Federated Learning. CoRR abs/1908.07420 (2019) - [i5]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Assessing the Impact of a User-Item Collaborative Attack on Class of Users. CoRR abs/1908.07968 (2019) - [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
- [b1]Yashar Deldjoo:
Video recommendation by exploiting the multimedia content. Polytechnic University of Milan, Italy, 2018 - [j5]Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo, Mehdi Elahi:
Current challenges and visions in music recommender systems research. Int. J. Multim. Inf. Retr. 7(2): 95-116 (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 - [c14]Yashar Deldjoo, Mihai Gabriel Constantin, Athanasios Dritsas, Bogdan Ionescu, Markus Schedl:
The MediaEval 2018 Movie Recommendation Task: Recommending Movies Using Content. MediaEval 2018 - [c13]Fatemeh Nazary, Yashar Deldjoo:
Movie Rating Prediction Using Multimedia Content and Modeling as a Classification Problem. MediaEval 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 - [c10]Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Peter Knees:
Multimedia recommender systems. RecSys 2018: 537-538 - 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 - [c6]Fabian Abel, Yashar Deldjoo, Mehdi Elahi, Daniel Kohlsdorf:
RecSys Challenge 2017: Offline and Online Evaluation. RecSys 2017: 372-373 - [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) - [i2]Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo, Mehdi Elahi:
Current Challenges and Visions in Music Recommender Systems Research. CoRR abs/1710.03208 (2017) - 2016
- [j3]Yashar Deldjoo, Reza Ebrahimi Atani:
A low-cost infrared-optical head tracking solution for virtual 3D audio environment using the Nintendo Wii-remote. Entertain. Comput. 12: 9-27 (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
- [j1]Saman Tahouri, Reza Ebrahimi Atani, Amir Hassani Karbasi, Yashar Deldjoo:
Application of connected dominating sets in wildfire detection based on wireless sensor networks. Int. J. Inf. Technol. Commun. Convergence 3(2): 139-160 (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
Coauthor Index
Alejandro Bellogín
aka: Alejandro Bellogín Kouki
aka: Alejandro Bellogín Kouki
[j23] [j22] [i36] [i32] [c59] [c58] [c57] [c56] [i27] [i24] [j17] [j16] [j15] [j14] [c52] [c51] [c49] [c48] [r2] [i22] [i17] [j11] [j9] [c44] [c43] [c42] [c41] [c40] [c38] [c36] [c35] [c34] [c33] [i15] [j8] [c30] [c29] [c28] [c27] [c26] [c25] [i13] [i12] [i11] [i10] [i9] [c24] [c18] [c17] [i7] [i6] [i5]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-23 21:21 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
