about_survey.html
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<h1>AppRecommender Survey</h1>
<h2>About</h2>
<p align="justify">This experiment aims to compare and validate automated application
recommendations produced by different strategies and algorithms tuning. We
believe that real users evaluation regarding the relevance of recommendations is
the most accurate data source for computing recommender system effectiveness.</p>
<br/>
<p align="justify">The engine that is being tested is a free software called <a
href="http://github.com/tassia/AppRecommender">AppRecommender</a>. It was
initially developed using the Debian Project infrasctructure, but the solution
is essentially distro-independent and can even be adapted to non GNU/Linux
systems given that there is available data for that.</p>
<a rel="facebox" href="static/images/apprec.png" title="AppRecommender Diagram">
<img style="float: right; margin: 10px;" alt="AppRecommender dataflow"
src="static/images/apprec.png" width="230px" /></a>
<br />
<p align="justify">The picture on the right gives an idea of the data workflow
for AppRecommender. The user provides a set of applications installed in his
system and the recommender suggests a set of programs that he might also
be interested in, based on the profile deduced from the his previous choices
and other similar users choices. The recommendations are composed using
classification and information retrieval techniques using
<a href="http://wiki.debian.org/Debtags">debtags</a>,
<a href="http://www.enricozini.org/sw/apt-xapian-index/">apt-xapian-index</a>,
<a href="http://popcon.debian.org/">Popcon</a> and <a
href="http://udd.debian.org/">UDD</a> as data sources.</p>
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