Applying Deep Learning-Based Personalized Item Recommendation for Mobile Service in Retailor Industry

Table 1

The comparison of recall results for different algorithms.

Experimental dataset	Wide and deep	DIN	FPMC	Item-KNN	BPR-MF	Proposed method
Dataset 1	0.7802	0.819	0.3901	0.2132	0.2309	0.7285
Dataset 2	0.6745	0.438	0.2904	0.4034	0.1035	0.8732
Dataset 3	0.7974	0.7252	0.1392	0.2972	0.2427	0.8029
Dataset 4	0.7189	0.5013	0.2158	0.4822	0.2521	0.8561