چکیده مقاله
The implementation of deep learning DL techniques within recommender systems RSS has enhanced their precision and ability to handle large datasets Nevertheless, this enhancement comes at a cost a lack of transparency, which raises significant issues about the interpretability of the model Here, we offer a review that aims to analyze the state of the art AI explanations provided for deep learning based recommender systems The review classifies the methods and frameworks into two primary types of explainability: intrinsic and post hoc It also addresses different explanation strategies including graph based, example based, and text based techniques In addition, we describe the common deep learning architectures applied in recommender systems like CNNs, RNNs, GNNs, and Transformers, and discuss how these models interact with various techniques of explainability Besides, our review reveals other important gaps, including the balance between accuracy and interpretability, limits on scalability, social issues like bias and opacity, or transparency among other ethical issues Lastly, it focuses on the designed user centered, universal and ethically aligned methods of explainability which are tailored to the needs of users The goal of these insights is to aid researchers and practitioners in developing more trustworthy and transparent recommender systems
کلیدواژهها
نویسندگان
Narjes Badpar
Department of Computer, CT C , Islamic Azad University, Tehran, Iran
Azita Shirazipour
Department of Computer, CT C , Islamic Azad University, Tehran, Iran
Seyed Javad Mirabedini
Department of Computer, CT C , Islamic Azad University, Tehran, Iran
شیوه ارجاع
Badpar, Narjes and Shirazipour, Azita and Mirabedini, Seyed Javad,1404,Recent Advances and Open Challenges in Explainable AI for Deep Learning-based Recommender Systems,The Second National Conference on the Era of Technology Explosion: Artificial Intelligence, a Transformation in Industry, Trade, and Supply Chain,Tabriz
ارائهشده در
مجموعه مقالات دومین کنفرانس ملی عصر انفجار تکنولوژی؛ هوش مصنوعی، تحولی در صنعت، تجارت و زنجیره تامین17 مهر 1404 · تبریز