Exact(6)
Nevertheless, user profiles and preferences cannot represent the Complicated Dependencies and Long-Distance Interventions in the game props recommendation tasks.
The cold-start problem is most prevalent to affect the accuracy and reasoning of recommendation tasks, since new users or items have no side information in recommendation domains.
At 100Credit, financial product recommendation not only considers user interest (as in traditional recommendation tasks), but also considers the risk level of users.
We randomly generate 100 route recommendation tasks in each city and assign each task to its top five eligible workers to get the best route of each task.
The Matrix Factorization (MF) technique has been demonstrated to be effective especially for personalized recommendation tasks [34], and it has been previously applied for drug target interaction prediction [5 7].
The experimental results on image classification and tag recommendation tasks on MIRFLICKR and NUS-WIDE datasets show that our parallelized fast optimization algorithm can achieve comparable or even better performance than the other examined methods, while speeds up the original optimization algorithm 20 110 times.
Similar(53)
As future work, we plan to analyze the proposed set of feature extraction techniques with other recommender algorithms, including those specific for the item recommendation task and optimization of personalized rankings, such as the BPR (Bayesian Personalized Ranking) [31], CliMF (Collaborative Less-is-More Filtering) [32], and TFMAP (Tensor Factorization for MAP Maximization) [33].
This makes our recommendation task difficult.
Then, the game props recommendation task can be cast into an MIML prediction problem.
Following this update rule, the MIML approach will minimize the ranking errors on the recommendation task.
In [66], authors propose to use the recommendation task for evaluating purposes.
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