Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Framework for Evaluating Snippet Generation for Dataset Search   Reusing existing datasets is of considerable significance to researchers and
developers. Dataset search engines help a user find relevant datasets for
reuse. They can present a snippet for each retrieved dataset to explain its
relevance to the user's data needs. This emerging problem of snippet generation
for dataset search has not received much research attention. To provide a basis
for future research, we introduce a framework for quantitatively evaluating the
quality of a dataset snippet. The proposed metrics assess the extent to which a
snippet matches the query intent and covers the main content of the dataset. To
establish a baseline, we adapt four state-of-the-art methods from related
fields to our problem, and perform an empirical evaluation based on real-world
datasets and queries. We also conduct a user study to verify our findings. The
results demonstrate the effectiveness of our evaluation framework, and suggest
directions for future research.

29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin