Πλοήγηση ανά Θέμα "Recommender systems"
Αποτελέσματα 1-8 από 8
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AMiner Citation-Data Preprocessing for Recommender Systems on Scientific Publications
(2021)Recommender Systems (RS) are used to find user's interested items among a huge amount of digital information, recently called Big Data, with the purpose of making valuable personalized recommendations. These systems use ... -
Digital image processing: Clinical applications and challenges in cosmetics
(2016)Digital image processing and analysis of medical images can effectively support medical diagnosis with valuable tools including automatic detection, recognition segmentation and measurement of visible entities of interest. ... -
A game theoretic framework for data privacy preservation in recommender systems
(2011)We address the fundamental tradeoff between privacy preservation and high-quality recommendation stemming from a third party. Multiple users submit their ratings to a third party about items they have viewed. The third ... -
Hyper-parameters Tuning of Artificial Neural Networks: An Application in the Field of Recommender Systems
(2022)In this work, we carry out the hyper-parameters tuning of a Machine Learning (ML) Recommender Systems (RS) which utilizes an Artificial Neural Network (ANN), called CATA++. We have performed tuning of the activation function, ... -
Layered evaluation in recommender systems: A retrospective assessment
(2014)Evaluation of recommender systems has only lately started to become more systematic, since the emphasis has long been on the experimental evaluation of algorithmic performance. Recent studies have proposed adopting a layered ... -
Propagating users' similarity towards improving recommender systems
(2014)In this paper we examine an advanced collaborative filtering method that uses similarity transitivity concepts. By propagating 'similarity' between users, in a similar way as with 'trust', we can significantly expand the ... -
A Recommender System based on Intuitionistic Fuzzy Sets for Software Requirements Prioritization
(2021)Requirements Prioritization (RP) is an important activity in requirements engineering aiming to give priority and order to requirements for implementation in the next version of a software project. RP is applied iteratively, ... -
Sequence adaptation via reinforcement learning in recommender systems
(2021)Accounting for the fact that users have different sequential patterns, the main drawback of state-of-the-art recommendation strategies is that a fixed sequence length of user-item interactions is required as input to train ...