Monday, July 12, 2021

MAKING CROSS-DOMAIN RECOMMENDATIONS BY ASSOCIATING DISJOINT USERS AND ITEMS THROUGH THE AFFECTIVE AWARE PSEUDO ASSOCIATION METHOD

Author :  John Kalung Leung

Affiliation :  George Mason University

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  11, 01, January, 2021

Abstract :

This paper utilizes an ingenious text-based affective aware pseudo association method (AAPAM) to link disjoint pseudo 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.

Keyword :  Behavioral Analysis, Emotion-aware Recommender System, Emotion prediction, Personality, Pseudo Users Association.

For More Detailshttps://aircconline.com/csit/papers/vol11/csit110108.pdf

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