LINGUIST List 13.3157

Mon Dec 2 2002

Software: MEAD - Multidocument Summarization Environment

Editor for this issue: James Yuells <>


  1. Dragomir Radev, MEAD - Multidocument Summarization Environment

Message 1: MEAD - Multidocument Summarization Environment

Date: Tue, 26 Nov 2002 18:16:38 +0000
From: Dragomir Radev <>
Subject: MEAD - Multidocument Summarization Environment

MEAD v3.07 released

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 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

- 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

- 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

- 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 or novelty detection.

- 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,

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
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