Critique

Hi Yu, Very nice page and being an area where I work, it's a super exciting read for me. First and foremost suggestion I would have is to read this paper http://dl.acm.org/citation.cfm?id=2645750 And if possible have a chat with Yidan, if you are interested to take this forward. Her entire thesis is on list reco.

Now coming to your work, few suggestions: 1. One major assumption you are probably implicitly making, that the lists are given as "list". Sorry for the cryptic term :-), but what I mean is, it's fairly challenging is to decide on length of list etc, what you call list features. Now often while recommending they are not known up-front. How this pose challenge to your algo? Do you see the result varying depending on how big a list is, it should. Also a study on how adoption actually gets affected, e.g. do people really care about what you recommend below a certain rank in a list?

2. Your algorithm is described well. But it will be much easy to understand if you can give a pseudo code, or since you implemented, actual code snippets.

3. It will be great to add right pointers to other relevant pages. For e.g Arthur made a page on general RS in last assignment. Referring to that would help interested user to follow more.

4. I will suggest a proof-reading as there are few quibbles but all said, it's a great step towards a very active research topic.

Hi Pirthu,

First thanks for your valuable advices. Actually, I get the dataset from Yidan and she also gave me some suggestions when I met problems on my work.

For your Critique:

1. Currently I only consider the length issues. My item-based algorithm is to do aggregation of all items' preference in a list and get the average preference value to represent the preference for the list. The reason to do average is considering the lists with large length will probably have more items that the user may be interested in. And I have not consider the order yet. However, I will follow your advices to elaborate the work more in the future.

2. I will add more contents in algorithm part.

3. I will add more external links.

4. I will do a proof reading before final draft.

Thanks again for your suggestions.

Best,

Yu Yan