Track: Data Mining
Paper Title:
Summarizing Email Conversations with Clue Words
Authors:
Abstract:
With the ever increasing popularity of emails, email overload
becomes a major problem for email users. Email summarization is one
way not only to solve this problem, but also to make use of one's
email corpus. In this paper, we propose a new framework for email
summarization. One novelty is to use a fragment quotation graph to try to
capture an email conversation. The second novelty is to use clue words to
measure the importance of sentences in conversation summarization. Based on
clue words and their scores, we propose a method called CWS, which is capable
of producing a summary of any length as requested by the user. We provide a
comprehensive comparison of CWS with various existing methods on the Enron
data set. Preliminary results suggest that CWS provides better summaries
than existing methods.
