Weekly Update

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This week I have been:

– Continuing experimenting with different hyperparameters of my models.

– Writing analysis based on the results.

– Continuing to work on the paper.

Weekly Update

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This week I have been:

– Continue with the implementation of my design.

– Set up a hyperparameter space to analyze how they affect the model.

– Test the model using different parameter combinations from that set.

– Continue with my paper.

Weekly Update

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For this week, I have been:

– Finish writing the first draft of my paper.

– Continue reading ways to determine implicit ratings from the data.

– Test and analyze the initial results of the recommender system.

Weekly Update

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This week I have been:

  • Working on the first draft of my paper.
  • Reading a research paper that use the same dataset as my project to derive a formula to get the implicit rating from the song play count.
  • Writing an initial version of the collaborative filtering algorithm, will try to test it next week.

Weekly Update

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These are the things I did for this week:

– Read Chapter 5 and did the quiz.

– Reworked the representation of the 2D matrix since the original method uses too much memory and not very practical.

– Started implementing the collaborative filtering algorithm for music recommendation.

Weekly Update

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This week I haven’t been able to get as much work done as I planned on. These are things that I did:

– Reread the proposal to answer some questions in the outline.

– Finish writing the outline.

– Make some minor changes to the program to reformat the data as suggested by Xunfei.

– Tried to run the program with the large dataset but wasn’t successful.

Weekly Update

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For this week, I have been mainly working on:

– Make a few changes on the coding environment for my project from last week for better efficiency.

– Follow Xunfei’s advice to consider some other music datasets. I eventually decided to use the Echo Nest Taste Profile Subset. This dataset is larger and more widely used than the LFM-1b dataset which I had been using.

– Design an efficient method to convert the original data into matrix form in order to use collaborative filtering.

Weekly Update

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This week I reviewed my project proposal and started setting up the coding environment. I also asked Xunfei to be my advisor for the project. During our meeting we discussed the project’s timeline for the first month and I made some changes in my timeline according to Xunfei’s suggestions. I’m also preparing for the project presentation in the next class.

Last Week Update

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This week I haven’t been able to do a lot since I have a lot of exams in other classes as well. But I have been working mainly on reviewing everything I have accomplished in this class and drafting a quick notes for what I should prepare for in CS488.

Weekly Update – Proposal Final Version

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This week I have been reading the feedback of the second draft of my proposal. I’m working on revising the paper to complete the final version for the paper.

I also talked with Dave about the paper and adjust the timeline according to his suggestions.

Weekly Update

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For this week, I have been discussing with Dave about details of my proposal paper, especially what I need to add/edit for the second draft and the final draft. I have also been reading some new research papers that have implementations of collaborative filtering that I can learn from.

Weekly Update

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This week I haven’t been able to do much due to some travelling. However, I still managed to design some methods to improve the running time of the collaborative filtering algorithms. I also worked on editing the second draft of my proposal and have a lot of progress in that.

Weekly Update

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This week I have been reading some published papers that use the same dataset as the one I use for this project. My purposes for doing this are to know the conclusions other people have made using the dataset and to examine the methods that they used. I found that some research projects used this dataset for investigating the diversity of different countries through listening habits and music recommendation with cultural context. I haven’t looked into the papers about music recommendation in detail but I plan to do that when I have the time. I think this will help a lot because they are using the same dataset that I will be using.

Weekly Update

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This week I asked Dave to be the advisor for my project. Dave suggested that I could explore the project in more ways such as having other ways to determine the similarity between two users and seeing what would work best. Dave also suggested some methods for optimization as one of the concerns of my project is that it doesn’t scale well with large amounts of data. Thus, if the implementation takes too long to generate recommendations, I will find ways to extract only a subset of the data, or come up with less intensive methods to calculate the similarity without losing much of the accuracy.

In addition, this week I also reread the first draft of my proposal and start working on the second draft.

Weekly Update

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This week, I met with Xunfei to talk about my project and have been working on finishing the first draft of my proposal. Now I will plan on having a 4-week plan and find a advisor for my project to schedule a meeting time.

Weekly Update

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For this week, I have been mainly working on my proposal for the project. I have been writing the introduction to my proposal and drawing up diagrams to make my project easier to understand. I also reviewed my paper about related work to see if there was anything I would like to make changes to. I also tried to come up with a timeline; however, so far is it still not finalized as I haven’t been able to predict precisely how much time I would spend on each task.

In addition, I also looked at the proposal criticism part of the slides to see whether anything needed improving.

Finally, I have also looked at the papers I have read, and picked out some of them for more careful reading (second/third time).

Weekly Update

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This week I’m focusing on my project, which is to build a method for building music recommendation using collaborative filtering. To do that I am currently reading papers about collaborative filtering in more details and comparing different techniques for collaborative filtering to determine what would work best for my project.

Weekly Update

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For this week I have been reading the research papers that are relevant to my topic and take notes of them. I still need to work on narrow down the scopes of my topics as a couple of them may not be feasible to complete over one semester.

I have also finished with making an annotated bibliography for each of the topics and will update them regularly as I find more relevant resources.