Trust in Recommender Systems a historical overview and recent developments

This document provides an overview of trust in recommender systems and discusses their historical development and recent advances. It begins with an introduction to information overload and the differences between information retrieval and information filtering. It then describes content-based filtering techniques and their weaknesses, particularly for recommending non-text items like movies and songs that require time-consuming human tagging. The document also discusses collaborative filtering recommender systems and the need for trust-aware filtering that considers users' trust in other users and in the recommendations.