Hypothesis-Based Collaborative Filtering

Download or read book Hypothesis-Based Collaborative Filtering written by Amancio Bouza and published by Lulu.com. This book was released on 2012-04-16 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems have emerged to help individuals with finding interesting products. As a result, the consumer welfare enhances due to the increased product variety. In other words, recommender systems are essential for increasing consumers welfare, which ultimately leads to an increase of economic and social welfare.Typically, recommender systems use the collective wisdom of individuals for exposing individuals to products which best fits their preferences. More precisely, the most like-minded individuals are considered by the recommender system to provide individuals recommendations. This is commonly referred to as collaborative filtering.In this dissertation, we present hypothesis-based collaborative filtering (HCF) to expose individuals to products which best fits their preferences. HCF retrieves like-minded individuals based on the similarity of their hypothesized preferences by means of machine learning algorithms hypothesizing individuals' preferences.