[Fall2022] [CSE573] [Group Project] Semantic Web Mining

[Group:22][Project#4] - A Review of Deep Learning-Based Movie Recommendation Systems

Group Members

• Chinmay Bhale
• Truxten Cook
• Kritshekhar Jha
• Kumarage Tharindu Kumarage
• Kyle Otstot
• Paras Sheth

Problem Definition

• Recommender systems have proven to be a successful method of reducing information overload in light of the increasing volume of online information.
• In recent years, research on recommender systems and information retrieval has shown that deep learning has a wide-ranging impact. However, they still have issues when working with extremely sparse data or other problems like cold start
• The purpose of this review paper is to provide a comprehensive and systematic analysis of current research projects on recommender systems based on deep learning
• We will provide a detailed taxonomy along with summaries for state-of-the-art algorithms.
• We also plan to provide a perspective on the future trends and research challenges of deep learning in recommender systems

Reviewed SOTA's

• Supervised Learning
  • Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP).
  • Inductive Matrix Completion Using Graph Autoencoder.
• Self-Supervised Learning
  • Bootstrapping User and Item Representations for One-Class Collaborative Filtering (BUIR).
• Semi (Weak) Supervised Learning
  • MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation.
• Unsupervised Learning

Project Plan: Tasks, Deadlines, Division of Work

#	Task Description	Task Owner	Deadline	Status
1	Background Study & Literature Survey	Everyone	25-Oct	Completed
2	Project Proposal	Everyone	12-Oct	Completed
3	Brainstorm the taxonomy for the survey	Everyone	25-Oct	Completed
4	Understanding of the selected SOTA for Supervised Learning	Chinmay Bhale	25-Oct	Completed
5	Implement the selected SOTA for Supervised Learning	Chinmay Bhale	15-Nov	Completed
6	Understanding of the selected SOTA for Supervised Learning	Kritshekhar Jha	25-Oct	Completed
7	Implement the selected SOTA for Supervised Learning	Kritshekhar Jha	15-Nov	Completed
8	Understanding of the selected SOTA for Self Supervised Learning	Paras Sheth	25-Oct	Completed
9	Implement the selected SOTA for Self Supervised Learning	Paras Sheth	15-Nov	Completed
10	Understanding of the selected SOTA for Semi Supervised Learning	Tharindu Kumarage	25-Oct	Completed
11	Implement the selected SOTA for Semi Supervised Learning	Tharindu Kumarage	15-Nov	Completed
12	Understanding of the selected SOTA for Unsupervised Learning	Truxten Cook	25-Oct	Completed
13	Implement the selected SOTA for Unsupervised Learning	Truxten Cook	15-Nov	Completed
14	Understanding of the selected SOTA for Unsupervised Learning	Kyle Otsot	25-Oct	Completed
15	Implement the selected SOTA for Unsupervised Learning	Kyle Otsot	15-Nov	Completed
16	Comparative analysis & discussion	Everyone	20-Nov	Completed
17	Project Presentation	Everyone	14-Nov	Completed
18	Group Demo	Everyone	30-Nov	Completed
19	Final Report	Everyone	2-Dec	Completed