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This paper utilizes an ingenious text-based affective aware pseudoassociation method (AAPAM) to link disjoint users and items across differentinformation domains and leverage them to make cross-domain content-based andcollaborative filtering recommendations. This paper demonstrates that the AAPAMmethod could seamlessly join different information domain datasets to act asone without any additional cross-domain information retrieval protocols.Besides making cross-domain recommendations, the benefit of joining datasetsfrom different information domains through AAPAM is that it eradicates coldstart issues while making serendipitous recommendations.

Making Cross-Domain Recommendations by Associating Disjoint Users and Items Through the Affective Aware Pseudo Association Method