Critique

Hi Arthur,
Good work so far! You did a good job presenting your work today. It made understanding your page a lot easier after seeing you present.
Here are few comments/suggestions:

• In the 'Result' section of your page, you mention that "Content features do help to improve the nearest neighbour algorithm accuracy becasue of its ability to improve the cosine similiarty calculation." I know you have a link to the wikipedia page for cosine similarity but it would be better if you briefly explained what cosine similarity is and how content features help improve the nearest neighbour algorithm’s accuracy.
• From your result, the RMSE value for integrated data is higher than the RMSE value for original data in general. Isn't RMSE supposed to be minimized? Also, can you give me an insight into why RMSE increases with the number of neighbours? Please correct me if I'm wrong.
• You should also have your references in your wiki page and cite relevant sections in the text.
• And finally, I’ve noticed a lot of typos and grammatical errors in the page. Please try to fix them.

Thanks for your page. I enjoyed your work.

Best regards,
Adnan

Hi Adnan

Thanks for your review and suggestion. for the RMSE, I previously had the wrong result because during the coding process, I miscoded the column and row for their sparse matrix calculation so that the respective row are multiplied with respective row and resulted the wrong answer. However, I have already debugged it and rerun the experiement. The RMSE for the integrated one is better as you can see on the page as well as during today's presentation.

For the reason why RMSE increase along with the neighbour, I think it is because the more neighbour you have, the more content you have. However, the matrix will become increasingly sparse. And when the postive accuracy of more content is counter-balanced by the negative content effect: so called the sparse matrix effect, then you will have worse RMSE.

Regarding the typos, can you take an example? I have already used grammarly.com to help check the errors. maybe it just doesn't work...

Arthur

From your results section:
"Content features do help to improve the nearest neighbour algorithm accuracy becasue of its ability to improve the cosine similiarty calculation.
There are few similar typos, but nothing to worry about. Your content is good. Keep up the good work.