Existing Web search services fail in helping users with information needs that
are broad, vague, or hard to express through a set of keywords. This dissertation
investigates the use of retrieval techniques based on inter-document similarity,
either measured through the textual contents or the linkage between documents.
Unlike traditional retrieval approaches, which match documents against
keywords and produce one-dimensional ranked lists of results, techniques based
on inter-document similarity offer better support for results visualization, as well
as alternative ways of expressing information needs. A Portuguese Web search
engine has been extended with two inter-document similarity algorithms: result
set clustering and related pages. The system was evaluated in a user survey, which
has shown that both algorithms are well accepted.