  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.
