Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism

Table 5

Precision, recall, and of , , , and based on FilmTrust-1 dataset.

Algorithm	Metrics (%)	Recommended number
		2	4	6	8	10	12	14	16	18	20
EHC–CF	Precision	82.2555	83.8450	82.8444	82.2364	81.5371	81.2952	81.1014	81.0292	80.9482	80.9327
	Recall	34.3482	57.5925	73.4343	84.5687	91.3565	95.2834	97.2184	98.1894	98.6618	99.0253
		48.9674	68.2819	77.8552	83.3853	86.1669	87.7341	88.4304	88.7868	88.9306	89.0687
DTNM	Precision	85.2386	84.0522	83.0014	82.1382	81.6513	81.2537	81.0887	80.9642	80.9636	80.9419
	Recall	34.3415	57.7353	73.5729	84.4672	91.4840	95.2343	97.2034	98.1105	98.6805	99.0364
		48.9578	68.4510	78.0024	83.2855	86.2874	87.6891	88.4167	88.7155	88.9475	89.0788
K-CF	Precision	85.1992	84.1723	83.0559	82.2075	81.7250	81.3210	81.1107	81.0446	81.0157	80.9571
	Recall	34.3256	57.8176	73.6217	84.5388	91.5668	95.3132	97.2297	98.2083	98.7445	99.0555
		48.9351	68.5486	78.0539	83.3559	86.3654	87.7617	88.4407	88.8037	89.0050	89.0957
DN-VCA	Precision	85.8327	84.3690	83.3180	82.4043	81.7817	81.3914	81.1733	81.0943	81.0097	80.9695
	Recall	34.5804	57.9529	73.8548	84.7414	91.6301	95.3956	97.3045	98.2682	98.7368	99.0703
		49.2986	68.7090	78.3006	83.5556	86.4252	87.8376	88.5088	88.8580	88.9982	89.1092