no code implementations • 7 Jan 2022 • Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
Then we use an RNN on the spatial relations to predict the spatio-temporal relations of reviewers in the group.
no code implementations • 10 Nov 2021 • Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
Many studies proposed approaches based on user behaviors and review text to address the challenges of fraud detection.
no code implementations • 25 May 2021 • Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
Social reviews are indispensable resources for modern consumers' decision making.
no code implementations • 11 Jun 2020 • Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
However, the lack of trusted labeled data has limited the performance of the current solutions in detecting fraud reviews.
no code implementations • 10 Jun 2020 • Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
In this research, instead of focusing only on one component, detecting either fraud reviews or fraud users (fraudsters), vector representations are learnt for each component, enabling multi-component classification.
no code implementations • 26 Apr 2019 • Mohammad Adiban, Bagher BabaAli, Saeedreza Shehnepoor
In this study, an approach is proposed for normal/abnormal heart sound classification on the Physionet challenge 2016 dataset.
no code implementations • 10 Mar 2017 • Saeedreza Shehnepoor, Mostafa Salehi, Reza Farahbakhsh, Noel Crespi
Nowadays, a big part of people rely on available content in social media in their decisions (e. g. reviews and feedback on a topic or product).