LoginSignup
0
0

More than 5 years have passed since last update.

@badrabbit(BadRabbit)

》》MULTI-DOCUMENT SUMMARIZATION OF EVALUATIVE TEXT, journal version

Last updated at Posted at 2017-11-10

GENERAL

ABSTRACT

  • PROBLEM
    • A framework for summarizing a corpus of evaluative documents about a single entity by a natural language summary
  • Series of previous work by same first author
    • first paper: extract & organize evaluative info
    • 1st study: compared the two summarizers: extractive vs. abstractive. The summarizers have different strengths and weaknesses.
    • 2nd study: when corpus is controversial, Evaluative text abstraction tends to be more effective than extraction.
    • 3rd study: assessed the effectiveness of our user tailoring strategy. User tailored summaries are more informative than un-tailored ones.

TASK of TEXT SUMMARIZATION

  • a task of annual Document Understanding Conference, DUC (renamed to Text Analysis Conference (TAC) since 2008)
  • most of previous work focused on factual, edited text and biographies, for which the goal is extract & order the most informative sentences in a domain-independent way, while avoiding repetition
  • when documents contain inconsistent info, the summarizer needs to identify overlaps and inconsistencies and produce summary that explains those inconsistencies.
  • basic steps
    • extract & analyze the evaluations expressed in the corpus (been studied extensively)
    • summarize them (received less attention)
      • extraction-based summarizer: extract
  • a
0
0
0

Register as a new user and use Qiita more conveniently

  1. You get articles that match your needs
  2. You can efficiently read back useful information
  3. You can use dark theme
What you can do with signing up
Sign upLogin
0
0