Discourse Factors in Multi-document Summarization  Ani Nenkova
The over-abundance of information today, especially on-line, has
established the need for natural language technologies that can
help the user find relevant information; multi-document
summarization (MDS) and question answering (QA) are two
examples. The requirement in MDS and open-ended QA to produce
multi-sentential answers imposes the extra demand that the
output of such systems be a coherent discourse. The problem of
generating appropriate referring expressions to entities in
these texts is non-trivial, because different sentences are
taken from their original context and put together to form a
text. The new context of the summary often requires changes in
surface realization of the references, demanding the inclusion
of additional information or removal of redundant information.
Such changes can be implemented by gathering a collection of
possible references to an entity from the input documents and
then rewriting the references in the sente