@InProceedings{daume02gleans,
  author =       {Hal {Daum\'e III} and Abdesammad Echihabi and Daniel Marcu and Dragos Stefan Munteanu and Radu Soricut},
  title =        {{GLEANS}: A Generator of Logical Extracts and Abstracts for Nice Summaries},
  booktitle =    {Proceedings of the Second Document Understanding Conference (DUC 2002)},
  year =         {2002},
  address =      {Philadelphia, PA},
  month =        {July 11 -- 12},
  pages =        {9 - 14},
  abstract =     {
    We briefly describe GLEANS, a summarization system that uses four
    novel techniques for summarizing document collections.  (i) GLEANS
    first maps all documents in a collection into a canonical,
    database-like representation that makes explicit the main entities
    and relations in a document collection.  (ii) GLEANS also
    classifies each document collection into one of four categories:
    collections about a single person, single events, multiple events,
    and natural disasters.  (iii) For each type of document
    collection, GLEANS also generates from scratch, using predefined
    templates, the first two sentences in the abstract.  (iv) The rest
    of the summary is then generated by extracting from the database
    sentences that conform to a set of predefined schemas and by
    presenting them in an order that reflects coherence constraints
    specific to each collection category.
  },
  url = {http://pub.hal3.name/#daume-gleans}
}