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Table 1.

Aggregation methods.

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Table 1 Expand

Fig 1.

Architecture of the proposed memory-based CF method.

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Fig 1 Expand

Table 2.

Conceptual decision matrix X.

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Table 2 Expand

Table 3.

Conceptual normalized decision matrix R.

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Table 3 Expand

Table 4.

Conceptual weighted normalized decision matrix V.

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Table 4 Expand

Table 5.

Conceptual separation matrix V′.

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Table 5 Expand

Fig 2.

Euclidean distances to the ideal and negative-ideal solutions.

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Fig 2 Expand

Fig 3.

Experimental process with respect to input parameters, datasets, methods with & without TOPSIS, and measurements.

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Fig 3 Expand

Table 6.

Recommendation confusion matrix.

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Table 6 Expand

Fig 4.

Recall measure by number of recommendations on 100K MovieLens.

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Fig 4 Expand

Fig 5.

Recall measure by number of recommendations on 1M MovieLens.

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Fig 5 Expand

Fig 6.

Recall measure by number of recommendations on HetRec2011.

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Fig 6 Expand

Fig 7.

Recall measure by number of recommendations on FilmTrust.

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Fig 7 Expand

Fig 8.

Precision measure by number of recommendations on 100K MovieLens.

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Fig 8 Expand

Fig 9.

Precision measure by number of recommendations on 1M MovieLens.

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Fig 9 Expand

Fig 10.

Precision measure by number of recommendations on HetRec2011.

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Fig 10 Expand

Fig 11.

Precision measure by number of recommendations on FilmTrust.

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Fig 11 Expand

Fig 12.

F-measure by number of recommendations on 100K MovieLens.

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Fig 12 Expand

Fig 13.

F-measure by number of recommendations on 1M MovieLens.

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Fig 13 Expand

Fig 14.

F-measure by number of recommendations on HetRec2011.

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Fig 14 Expand

Fig 15.

F-measure by number of recommendations on FilmTrust.

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Fig 16.

Comparison of MAP for all methods using all datasets.

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Fig 16 Expand