A Sequential Recommendation with Local Optimal Partition Long-Short Term Interest
It is very important to identify both the user's long-term and short-term interest in sequential recommendation.Most of the existing models simply preset the short-term interest length,but the performance improvement is not obvious.For better model the user's long-term and short-term interest,this paper proposes a sequential reconmendation model with local optimal partition long-short term interest adopts a local optimal short-term interest length algorithm to automatically and adaptively search for the optimal short-term interest length,then designs an MLP layer to model long-term and short-term interests respectively.Through three experiments conduc-ted on a dataset,the model achieved competitive performance with the state-of-the-art models.
sequential recommendationMLPlong-short term interestlocal optimal
NETL
NSTL
万方数据
