A personality-aware recommendation system is a special type of recommendation system which imparts the recommendations based on the user’s personality and personality psychology. The personality-aware recommendation system is the better alternative to traditional recommendation systems, providing much data on user preferences. Personality-aware recommendation systems involve personality computing that enables the recommendation system to recognize the user predilections from different perspectives. In addition to the phrases involved in conventional recommendation systems such as rating phase, filtering phrase, recommendation phrase, personality aware recommendation system contains two more phrases such as personality measurement phrase and personality matching phrase. In the personality measurement phrase, user personality is determined by a personality assessment questionnaire and automatic personality recognition. In the personality matching phrase, the system matches the user personality type with similar items by lexical matching or fine-grained rules.
One of the classification schemes for personality-aware recommendation system for filtering is personality filtering is the process of neighborhood formation, and methods of personality filtering are personality neighborhood, matrix factorization. Other classifications are deep learning, personality matching, and hybrid personality filtering. Application of advanced recommendation systems is Friend Recommendations, Movie Recommendations, Music Recommendations, Image Recommendation, Academic Content Recommendation, Product Recommendations, Points of Interest Recommendations, and Game Recommendations. Personality-aware Recommendation Systems with high personality detection accuracy and personality information privacy are future advancements to be developed.