- Final Project Supplementary Materials: A zip file of your supplementary materials. You are required to include all the code for your project in the supplementary materials Your final write-up should be between 3 - 5 pages written as a research paper. Your final report should include the following: - Title, Author(s) - Abstract: It should not be more than 300 words. - Introduction: This section introduces the problem and your overall approach to the problem. - Background/Related Work: This section discusses relevant literature for your project. - Approach: This section details your approach to the problem. For example, this is the section where you would describe your recommendation methodology and why the selected metrics should provide better answers for your problem and data. You should be specific - you may want to include equations, figures, plots, etc. - Experiments: In this section, you describe: The dataset(s) you used How you ran your experiments (e.g. model configurations, learning rate, training time, etc.) The evaluation metric(s) you used Your results. show numbers, figures, tables, etc. relating to your evaluation metric(s) - Discussion and Conclusion: What have you learned? Suggest future ideas. - References and Team Contribution: Include references to all literature that informed your project work. The contribution of each team member should be added here. The final project write-up will be graded based on the following criteria: writing, methodology, discussion, visualization, and proper citations. Phase 4: Project Presentation [PLO C1 / CLO 3 / SO 3] Each team is expected to present their work in class. The presentation session should be between 8 and 10 minutes long. Students should practice their presentations to deliver them on time. After each presentation, there will be five minutes for questions and changing groups. The questions will be led by the course instructor although students may ask questions. The content of the presentation should reflect the work that each team accomplished in their project and is preferred to be aligned with the structure of the final project writeup 4/5 Data description and statistics: The distribution of cuisines in your dataset. The average number of reviews per restaurant? The distribution of rating values in your dataset (mostly positive, mostly negative, or balanced)? Feel free to add other interesting features or statistics about your data Small Dataset (per student): (should have al least 200 ratings) Combined Dataset (per group): List of all the restaurants and ratings as a csv file (an example of the dataset is uploaded on the blackboard) (should have al least 600 ratings) Phase 2: Project Milestone [PLO S1 / CLO 2 / SO 2] The purpose of the project milestone is to ensure that teams can complete their projects on time. For the milestone, you need to: - Have collected all your data - Have selected the recommendation methods and implemented one of the two models that you have selected. - Have dealt with the sparsity problem expected in most recommender data - Have your evaluation pipeline set up. Please submit one milestone per team (any member of your team can submit). Your milestone can be short (a single page). It should, at minimum, have the following headings. If you have done more than run a baseline, good job! You are free to add more details to the milestone if you want. Team: Names and university IDs of the member. Problem Description: What is the problem and how are you approaching it? (In this part, you can describe the sparsity problem and how it impacts your project) Methodology and Baseline: Describe your recommendation methodology (i.e. steps that you do). How do you approach various problems (e.g. similarity, sparsity, and prediction)? What are the model-based techniques that you selected? What other algorithms or metrics do you use with your data? Implementation Platform: What language, libraries, and platform have you used to implement your methodology and baseline metrics? Results: How well does your baseline work? What are the initial results? Phase 3: Final Submission [PLO S2 / CLO 2 / SO 2] The final submission of your project should be submitted once by any member of the team. It must include the following: - Final Project Writeup: A PDF file of your final report 3/5 Data description and statistics: The distribution of cuisines in your dataset. The average number of reviews per restaurant? The distribution of rating values in your dataset (mostly positive, mostly negative, or balanced)? Feel free to add other interesting features or statistics about your data Small Dataset (per student): (should have al least 200 ratings) Combined Dataset (per group): List of all the restaurants and ratings as a csv file (an example of the dataset is uploaded on the blackboard) (should have al least 600 ratings) Phase 2: Project Milestone [PLO S1 / CLO 2 / SO 2] The purpose of the project milestone is to ensure that teams can complete their projects on time. For the milestone, you need to: - Have collected all your data - Have selected the recommendation methods and implemented one of the two models that you have selected. - Have dealt with the sparsity problem expected in most recommender data - Have your evaluation pipeline set up. Please submit one milestone per team (any member of your team can submit). Your milestone can be short (a single page). It should, at minimum, have the following headings. If you have done more than run a baseline, good job! You are free to add more details to the milestone if you want. Team: Names and university IDs of the member. Problem Description: What is the problem and how are you approaching it? (In this part, you can describe the sparsity problem and how it impacts your project) Methodology and Baseline: Describe your recommendation methodology (i.e. steps that you do). How do you approach various problems (e.g. similarity, sparsity, and prediction)? What are the model-based techniques that you selected? What other algorithms or metrics do you use with your data? Implementation Platform: What language, libraries, and platform have you used to implement your methodology and baseline metrics? Results: How well does your baseline work? What are the initial results? Phase 3: Final Submission [PLO S2 / CLO 2 / SO 2] The final submission of your project should be submitted once by any member of the team. It must include the following: - Final Project Writeup: A PDF file of your final report 3/5