Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Target Type Identification for Entity-Bearing Queries   Identifying the target types of entity-bearing queries can help improve
retrieval performance as well as the overall search experience. In this work,
we address the problem of automatically detecting the target types of a query
with respect to a type taxonomy. We propose a supervised learning approach with
a rich variety of features. Using a purpose-built test collection, we show that
our approach outperforms existing methods by a remarkable margin. This is an
extended version of the article published with the same title in the
Proceedings of SIGIR'17.

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The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
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The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
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The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn