[Corpora-List] MEAD - multidocument summarization environment

[Dragomir R. Radev]

			 MEAD v3.07 released
			 -------------------

                http://www.summarization.com/mead

MEAD is a multi-document summarization system with multi-lingual
capabilities.  The MEAD system implements extractive
summarization, whereby summaries are produced by selecting a subset
of highly relevant sentences from the cluster's overall set of
sentences.  MEAD can summarize clusters of English documents on
most POSIX-conforming operating systems and can summarize
clusters of Mandarin Chinese documents on a subset of these
operating systems.

The MEAD system has been under development since 2000. Versions 1.0
and 2.0 were developed at the University of Michigan. Version 3.0 was
developed at a six-week workshop at the Johns Hopkins University.
Versions 3.01 through 3.06 were incremental improvements by the JHU
workshop team members.  With version 3.07, development of MEAD has
moved back to the University of Michigan.

MEAD 3.07 represents a major refactoring of previous MEAD
versions.  The current version supports all the functionality of
previous versions, but also has many new features.  Some of these
are:

- Version 3.07 is much more configurable than previous versions of
  MEAD.  It allows for both system-wide and user-specific
  configuration files.

- It has a simplified user interface.  Previous versions required the
  user to manually edit a mead.config file and use a combination of
  Unix shell commands to produce summaries.  While the current version
  still supports this interface, MEAD 3.07 has a single script
  interface that essentially eliminates the need for manual editing of
  mead.config files.

- MEAD Eval, a previously free-standing tool for evaluating
  summarizers, has been incorporated with the current version of MEAD.
  This allows users to evaluate existing summaizers, as well as
  evaluate the performance of the base MEAD system and any user
  modifications.  MEAD Eval supports co-selection (percent agreement,
  precision, recall, Kappa) and content-based evaluation metrics (such
  as word overlap and longest common subsequence), as well as relative
  utility.

- MEAD uses an extensive collection of custom Perl modules that may be
  suitable for use in many natural language applications, including
  for example, question answering.

- Random and lead-based summarizers have been incorporated into the
  MEAD framework.  These summarizers provide useful examples of how to
  create new MEAD modules.

- The documentation for the current version has been expanded,
  and now includes a significant number of example use cases and
  tutorials for customizing each of MEAD's modules.

To download MEAD, including documentation, and view online docs,
visit:
        http://www.summarization.com/mead

People who have worked on MEAD include:

Dragomir Radev, Sasha Blair-Goldensohn, John Blitzer, Arda Celebi,
Elliott Drabek, Wai Lam, Danyu Liu, Hong Qi, Horacio Saggion, Simone
Teufel, Michael Topper, Adam Winkel