60 citations · 70 across the 3 of their papers we have counts for
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cs.IR2021★ 60 cited
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models
Alexander Dallmann, Daniel Zoller, Andreas Hotho
At the present time, sequential item recommendation models are compared by calculating metrics on a small item subset (target set) to speed up computation. The target set contains…
cs.IR2017★ 10 cited
Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time
Alexander Dallmann, Alexander Grimm, Christian Pölitz +2
Recently, Recurrent Neural Networks (RNNs) have been applied to the task of session-based recommendation. These approaches use RNNs to predict the next item in a user session based…