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TRec: Sequential Recommender Based On Latent Item Trend Information
Our study demonstrates the importance of item trend information in recommendation system designs, and our method also possesses great efficiency which enables it to be practical in real-world scenarios.
The LAIX Systems in the BEA-2019 GEC Shared Task
In this paper, we describe two systems we developed for the three tracks we have participated in the BEA-2019 GEC Shared Task.
Ranked #17 on
Grammatical Error Correction
on BEA-2019 (test)
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