Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DCDIR: A Deep Cross-Domain Recommendation System for Cold Start Users in
  Insurance Domain   Internet insurance products are apparently different from traditional
e-commerce goods for their complexity, low purchasing frequency, etc.So, cold
start problem is even worse. In traditional e-commerce field, several
cross-domain recommendation (CDR) methods have been studied to infer
preferences of cold start users based on their preferences in other domains.
However, these CDR methods could not be applied into insurance domain directly
due to product complexity. In this paper, we propose a Deep Cross Domain
Insurance Recommendation System (DCDIR) for cold start users. Specifically, we
first learn more effective user and item latent features in both domains. In
target domain, given the complexity of insurance products, we design meta path
based method over insurance product knowledge graph. In source domain, we
employ GRU to model user dynamic interests. Then we learn a feature mapping
function by multi-layer perceptions. We apply DCDIR on our company datasets,
and show DCDIR significantly outperforms the state-of-the-art solutions.

5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math