Suggestions

Hi Sun,

very informative and easy to understand. And I am actually very interested in how could amazon always guess out exactly the book I am interested in. And now I know.

1. Can you introduce more about Textual Semantic Similarity and Weighted textual matrix factorization, although you introduced those, but still did not touch how it works.

2. I think you might need more info about two level Matrix Factorization, the first paper seems to have more information than this two level one

3. Do you want to make a conclusion to compare about the two different solutions?

Dear Dandan

Thank you for your great support and suggestions regarding my wiki pages.

I have already added the experimental result part at the end of the wiki page.

Regarding your suggestion 1 and 2, for suggestion 1, I think TSS and WTMF will account for a large portion of paragraph if elaborated in detail. In fact, the second paper just use it for the implicit information generation and it is not the most novelty point in the paper. I think the heuristic in this paper is to combine the implicit data into matrix factorization to solve the cold start problem and matrix factorization has already been detailed explained in the previous paper. So I didn't put too much emphasis on the second paper. Thank you

Regards Arthur