Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Business Taxonomy Construction Using Concept-Level Hierarchical
  Clustering   Business taxonomies are indispensable tools for investors to do equity
research and make professional decisions. However, to identify the structure of
industry sectors in an emerging market is challenging for two reasons. First,
existing taxonomies are designed for mature markets, which may not be the
appropriate classification for small companies with innovative business models.
Second, emerging markets are fast-developing, thus the static business
taxonomies cannot promptly reflect the new features. In this article, we
propose a new method to construct business taxonomies automatically from the
content of corporate annual reports. Extracted concepts are hierarchically
clustered using greedy affinity propagation. Our method requires less
supervision and is able to discover new terms. Experiments and evaluation on
the Chinese National Equities Exchange and Quotations (NEEQ) market show
several advantages of the business taxonomy we build. Our results provide an
effective tool for understanding and investing in the new growth companies.

27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess