協調フィルタ方式による個人への物件推薦アルゴリズム

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

Hybrid Collaborative Filtering Based on Probabilistic Prototype

Collaborative filtering recommender systems-recommend items by identifying other users with similar taste and use their opinions for recommendation. In this paper the concepts of Content-Boosted Collaborative Filtering algorithm is discussed and proposed for modification in the existing approach using probabilistic measures to improve the performance. The methodology using Probabilistic Prototype used for predictions have been discussed. The Formulas that were used to implement these models including Bayes conditional probability, rating, Significance Weighting Factor, Harmonic Mean Weighting and Self-Weighting an