Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient and Effective Single-Document Summarizations and A
  Word-Embedding Measurement of Quality   Our task is to generate an effective summary for a given document with
specific realtime requirements. We use the softplus function to enhance keyword
rankings to favor important sentences, based on which we present a number of
summarization algorithms using various keyword extraction and topic clustering
methods. We show that our algorithms meet the realtime requirements and yield
the best ROUGE recall scores on DUC-02 over all previously-known algorithms. We
show that our algorithms meet the realtime requirements and yield the best
ROUGE recall scores on DUC-02 over all previously-known algorithms. To evaluate
the quality of summaries without human-generated benchmarks, we define a
measure called WESM based on word-embedding using Word Mover's Distance. We
show that the orderings of the ROUGE and WESM scores of our algorithms are
highly comparable, suggesting that WESM may serve as a viable alternative for
measuring the quality of a summary.

17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th