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Found 4 papers, 1 papers with code
Sequential Item Recommendation in the MOBA Game Dota 2
We find that SIR models can be employed effectively for item recommendation in Dota 2.
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models
Then we evaluate all models on a target set sampled by the two different sampling strategies, uniform random sampling and sampling by popularity with the commonly used target set size of 100, compute the model ranking for each strategy and compare them with each other.
ClaiRE at SemEval-2018 Task 7 - Extended Version
Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75. 11% for the first subtask and 81. 44% for the second.
Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time
Recently, Recurrent Neural Networks (RNNs) have been applied to the task of session-based recommendation.
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