\chapter{Summary and future work}

The IntFilter project started out boldly, with many members and
a promising future. Many of the initial ambitions, however, were
abandoned for trivial reasons; as the number of active workers waned
the wide selections of ideas was cut down by the necessity to choose.

After an abandoned software project and initial experiments, the
\PEFNA\ News filtering prototype was designed and developed.
It allowed the user to create arbitrary categories of texts, and
performed filtering by estimating the distances between the user's
unread texts and the categories. Field tests of the \PEFNA\ system
revealed that it was able to perform as intended, but also that the
structure of natural language made classification more intricate than
was expected of a keyword search.

At the time of this writing, late 1996, the project is not scheduled
for any continued activity. However, as a note to fellow researchers
in the field we would like to ventilate a few ideas below, ideas which
emerged when it was too late to reconsider the
choices already made.

Work on the visualization of retrieved information is already being
pursued in several places. The interested reader may consult 
\cite{card96,catarci96,eick96,gershon96}
for a comprehensive rundown on this fascinating topic.


\section{Epilogue}

A lot of things can be measured in a text but what is easily computed
appears to have only a weak relation to how human readers estimate a
text. The span between computer analysis and human judgement and
intuition is still very wide.

What can be done is what almost everybody else in filtering are doing;
to look at the words in the texts and make the assumption that two
interesting texts on the same topic will share a significantly large
vocabulary. This is a superficial comparison, which does not analyse
or understand the text, and without the ability to perform analogy,
inference or paraphrasing. Searching for keywords only covers a part
of the human interest space, since we can't easily model such concepts
as `a letter from the editor', `a funny thing happened on the way to
Rome' or `one more of these virus hoaxes today and I'll scream'.

What appears to be underestimated in the problem area of text
classification and filtering, is the remarkable ability of ordinary
people to make intuitive decisions based on whatever information is
at hand. But why not use the computer to perform tasks it is good at,
like visualization of a data space; to hide and expose information and
place this magnifying lens in the hands of user?

To be specific, rather than having the computer make the decision if
the message is worth reading, let the reader continue to make the
decision, but have the computer supply the relevant information on
which to ground this decision in a swift and timely manner. Replace
the tedious list of subject lines with a threedimensional view of the
entire newsgroup. Let the user select long messages, short messages,
heavily cited articles at the twitch of a finger. As soon as a message
has been read, allow the user to immediately select other texts close
to the one just read.


%% Sid 33 Chapter 4 
%% \section{Epilogue}


This study has evolved to support the hypothesis of graphical presentation
as a means to help readers find interesting texts. The combination of
the computer's possibility to sort and display information graphically and
the human ability to recognize patterns and discriminate graphic
properties will open new possibilities to help us take advantage of the
information now sunk in the ocean of Internet.

Future work on this topic ought to focus on different ways to display
the properties of a text that carry meaning to the reader and on the
human ability to visually discriminate them.

It is however important to take in consideration that readers are
different.  Physiologically they have different ability to
discriminate different kinds of perceptions and intellectually they
find different properties in a text more or less important for judging
the interest.

To test our hypothesis it would be interesting to conduct a longer
user test with a further developed prototype containing graphical
presentation of different properties in texts. The prototype should be
flexible so that the user can adjust it to his or her actual situation
and preferences. If the study goes on for at least two months,
preferably more, there is a chance that the user really adapts his/her
behaviour to the tool and finds out the best way to use it. If
different users, working under different conditions, take part in the
test the flexibility of the prototype could provide a good picture of
useful support functions.

The prototype could for instance have the following functions:
\begin{itemize}
\item The user can give keywords that are preferred or not preferred in
texts. Preferred words are shown green, not preferred are shown red.

\item The user can give maximum and minimum length of texts.

\item The user can give maximum (or minimum) ratio of cited text.

\item The texts are shown graphically as circles or cylinders with their size 
illustrating length, the colour telling if there are preferred or not
preferred keywords.

\item The user can choose to look closer to one part of the
presentation, e.g. one or two categories.

\item When pointing at a text symbol, the closeness to a category is
shown by arrows and the layout can be examined by displaying the text
in "stamp size" where the subject line is readable and the keywords
shown in colour.
\end{itemize}

From any of these presentations it should be possible to click and
read the text, to drag a text to a folder for later reading, to drop
it in the waste paper basket or in a letter box to some other person,
adding a comment.

%% Eva R \FAAR


