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Applied Artificial Intelligence
An International Journal
Volume 27, 2013 - Issue 3
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Original Articles

HYBRID PROFILING FOR HYBRID MULTICRITERIA RECOMMENDATION BASED ON IMPLICIT MULTICRITERIA INFORMATION

Wichian Premchaiswadi Graduate School of Information Technology in Business, Siam University, Bangkok, ThailandCorrespondence[email protected]
&
Pitaya Poompuang Graduate School of Information Technology in Business, Siam University, Bangkok, ThailandCorrespondence[email protected]
Pages 213-234 | Published online: 14 Mar 2013

Figures & data

FIGURE 1 A hybrid profiling framework. (Color figure available online.)

FIGURE 1 A hybrid profiling framework. (Color figure available online.)

TABLE 1 Example Data of the Traditional User Profiles, User-Item Ratings (UIR)

TABLE 2 Example Data in Item-Attribute Binary Values (IAB)

TABLE 3 Example Data in the User-Item-Attribute Binary and Ratings (UIABR)

TABLE 4 Example Data in the User-Attribute Weights (UAW)

TABLE 5 Example Data in User-Item-Attribute Weights (UIAW)

TABLE 6 Example Data in the Item-Attribute Weights (IAW)

FIGURE 2 The MAE of the SUBCF, MAUBCF, SIBCF, MAIBCF, and UAB. (Color figure available online.)

FIGURE 2 The MAE of the SUBCF, MAUBCF, SIBCF, MAIBCF, and UAB. (Color figure available online.)

TABLE 7 Averages of MAE Evaluated from Whole Possible Neighbor

TABLE 8 The Precision Scores in the Case of Top-1, 3, 5 and 7 at the Point of 10 Neighbor Sizes with Thresholds 3 and 4

TABLE 9 The Percentage of Precision Improvement from the Baseline of All Multicriteria Approaches

TABLE 10 The Precision Scores in the Case of Top-1, 3, 5 and 7 at the Point of 1 Neighbor Sizes with Thresholds 3 and 4

TABLE 11 The Percentage of Precision Improvement from the Baseline of the UAB Approach

TABLE 12 The Precision of UAB against UIM Method Based on 1 Neighbor Size with Threshold 3 and 4

TABLE 13 The Percentage of Precision Improvement from the UAB Approach of the UIM Approach

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