  This paper utilizes an ingenious text-based affective aware pseudo
association method (AAPAM) to link disjoint users and items across different
information domains and leverage them to make cross-domain content-based and
collaborative filtering recommendations. This paper demonstrates that the AAPAM
method could seamlessly join different information domain datasets to act as
one without any additional cross-domain information retrieval protocols.
Besides making cross-domain recommendations, the benefit of joining datasets
from different information domains through AAPAM is that it eradicates cold
start issues while making serendipitous recommendations.
