• P. Jenifer
• A. Shakeela Joy
• Merry Ida

A recommendation system is an integral part of any modern online shopping or social network platform. The product recommendation system as a typical example of the legacy recommendation systems suffers from two major drawbacks: recommendation redundancy and unpredictability concerning new items (cold start). These limitations take place because the legacy recommendation systems rely only on the user’s previous buying behavior to recommend new items. Incorporating the user’s social features, such as personality traits and topical interest, might help alleviate the cold start and remove recommendation redundancy. Therefore, in this article, we propose Meta-Interest, a personality-aware product recommendation system based on user interest mining and metapath discovery. Meta-Interest predicts the user’s interest and the items associated with these interests, even if the user’s history does not contain these items or similar ones. This is done by analyzing the user’s topical interests and, eventually, recommending the items associated with the user’s interest. The proposed system is personality-aware from two aspects; it incorporates the user’s personality traits to predict his/her topics of interest and to match the user’s personality facets with the associated items. The proposed system was compared against recent recommendation methods, such as deep-learning-based recommendation system and session-based recommendation systems.p.

Meta-Interest, User Interest Mining, Metapath discovery, Recommendation System, deep learning

"Personalised Product Recommendation System basing the User Interest Mining with Metapath discovery", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.a418-a421, September-2022, Available :http://www.jetir.org/papers/JETIR2209041.pdf

"Personalised Product Recommendation System basing the User Interest Mining with Metapath discovery", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppa418-a421, September-2022, Available at : http://www.jetir.org/papers/JETIR2209041.pdf