Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Human Curation and Convnets: Powering Item-to-Item Recommendations on
  Pinterest   This paper presents Pinterest Related Pins, an item-to-item recommendation
system that combines collaborative filtering with content-based ranking. We
demonstrate that signals derived from user curation, the activity of users
organizing content, are highly effective when used in conjunction with
content-based ranking. This paper also demonstrates the effectiveness of visual
features, such as image or object representations learned from convnets, in
improving the user engagement rate of our item-to-item recommendation system.

19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int