Using Content-Based Filtering for Recommendation

386 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Recommender systems survey (2013, background): “Content-based filtering [131,11,158] makes recommendations based on user choices made in the past (e.”
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery (2020, unknown): “Over the past decades, a plethora of research has been devoted to the development of recommendation algorithms, from classical techniques (Van Meteren & Van Someren, 2000; Sarwar et al., 2001; Koren et al., 2009) to machine learning (He et al., 2017; Wang et al., 2016; Rendle & Schmidt-Thieme,…”
New Recommendation System Using Reinforcement Learning (2005, background): “Robin van Meteren and Maarten van Someren proposed PRES [3] that use content-based filtering techniques to suggest document that relevance to user profile.”
Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval (2008, unknown): “In Section 4, we make our conclusions.”