- E-postmehdi.elahi@uib.no
- Telefon+47 55 58 91 79
- BesøksadresseFosswinckels gate 6Lauritz Meltzers hus5007 Bergen
- PostadressePostboks 78025020 Bergen
Lærebok
- (2022). Social Data Analytics. CRC Press.
Vitenskapelig artikkel
- (2024). Predicting movies’ eudaimonic and hedonic scores: A machine learning approach using metadata, audio and visual features. Information Processing & Management.
- (2023). Hybrid recommendation by incorporating the sentiment of product reviews. Information Sciences. 738-756.
- (2023). Benchmarking equivariance for Deep Learning based optical flow estimators. Signal processing. Image communication.
- (2022). Parallel Fractional Stochastic Gradient Descent With Adaptive Learning for Recommender Systems. IEEE Transactions on Parallel and Distributed Systems. 470-483.
- (2022). News Images in MediaEval 2022. CEUR Workshop Proceedings.
- (2022). Developing and Evaluating a University Recommender System. Frontiers in Artificial Intelligence.
- (2022). Adaptive trust-aware collaborative filtering for cold start recommendation. Behaviormetrika.
- (2022). A Convolutional Attention Network for Unifying General and Sequential Recommenders. Information Processing & Management.
- (2021). Responsible media technology and AI: challenges and research directions. AI and Ethics.
- (2021). News Images in MediaEval 2021. CEUR Workshop Proceedings.
- (2021). Investigating the impact of recommender systems on user-based and item-based popularity bias. Information Processing & Management.
- (2020). From Trustworthy Data to Trustworthy IoT: A Data Collection Methodology Based on Blockchain. ACM Transactions on Cyber-Physical Systems.
- (2020). Addressing the New Item problem in video recommender systems by incorporation of visual features with restricted Boltzmann machines. Expert Systems.
Vitenskapelig antologi/Konferanseserie
- (2023). Addressing Popularity Bias in Recommender Systems: An Exploration of Self-Supervised Learning Models. Association for Computing Machinery (ACM).
- (2021). MORS 2021: Multi-Objective Recommender Systems 2021. Association for Computing Machinery (ACM).
Mastergradsoppgave
- (2023). Using content- and behavioural data for recommendations in the Norwegian news market.
- (2023). Personalized Recommendations of Upcoming Sport Events.
- (2023). Media Analytics for Personalization in Advertisement.
- (2022). Movie recommendation based on stylistic visual features.
- (2021). Video Recommendations Based on Visual Features Extracted with Deep Learning.
- (2021). Novel Methods Using Human Emotion and Visual Features for Recommending Movies.
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
- (2023). The Interplay between Food Knowledge, Nudges, and Preference Elicitation Methods Determines the Evaluation of a Recipe Recommender System.
- (2023). Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study. 6 sider.
- (2022). Mitigating Popularity Bias in Recommendation: Potential and Limits of Calibration Approaches. 9 sider.
- (2022). Hybrid Recommendation of Movies based on Deep Content Features.
- (2021). Recommending Videos in Cold Start With Automatic Visual Tags.
- (2021). MORS 2021: 1st Workshop on Multi Objective Recommender Systems.
- (2021). Beyond Algorithmic Fairness in Recommender Systems.
- (2020). Visually-Aware Video Recommendation in the Cold Start. 5 sider.
- (2020). Towards Generating Personalized Country Recommendation. 6 sider.
- (2020). Simulating the Impact of Recommender Systems on the Evolution of Collective Users' Choices. 6 sider.
Poster
- (2022). Capacity-Based Trust System in Untrusted MEC Environments.
- (2021). Enhanced Movie Recommendation Incorporating Visual Features.
- (2021). Beyond Algorithmic Fairness in Recommender System.
Vitenskapelig oversiktsartikkel/review
- (2021). Towards Responsible Media Recommendation. AI and Ethics. 12 sider.