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updated docs, added recommendation to tutorial

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This commit is contained in:
Michael Hunger
2011-04-04 12:07:01 +02:00
parent ff7484b24b
commit 44e667d834
2 changed files with 58 additions and 21 deletions
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4
src/docbkx/reference/programming-model/aspectj.xml
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@@ -35,7 +35,9 @@
</para>
<para>
Eclipse and STS support AspectJ via the AJDT plugin which can be installed from the update-site:
<ulink url="http://download.eclipse.org/tools/ajdt/36/update/">http://download.eclipse.org/tools/ajdt/36/update/</ulink>
(or for the latest development snapshot of the plugin
<ulink url="http://download.eclipse.org/tools/ajdt/36/dev/update">http://download.eclipse.org/tools/ajdt/36/dev/update</ulink>).
</para>
<para>
The AspectJ support in IntelliJ IDEA lacks some of the features. JetBrains is working to improve the situation

75
src/docbkx/tutorial/recommendations.xml
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@@ -3,25 +3,60 @@
<chapter id="tutorial_recommendations">
<title>Movies! Friends! Bargains! - Recommendations</title>
<para>
In the last part of this exercise we wanted to add recommendations to the app. One obvious recommendation is movies that our friends liked
(and their friends too, but with less importance). The second was recommendations for new friends that also liked the movies that we liked most.
</para><para>
Doing this kind of ranking algorithms is really fun with graph databases. They are applied to the graph by traversing it in a certain order, collecting information
on the go and deciding which paths to follow and what to include in the results.
</para><para>
Lets say I'm only interested in the top 10 recommendations each.
</para><para>
<programlisting language="java" ><![CDATA[
// TODO Work In Progress 1/path.length()*stars
user.breathFirst().relationship(FRIEND, OUTGOING).relationship(RATED, OUTGOING).evaluate(new Evaluator(Path path) {
if (path.length > 5) return EXCLUDE_AND_STOP;
Relationship rating = path.lastRelationship();
if (rating.getType().equals(RATED)) {
rating.getProperty()
return INCLUDE_AND_STOP;
}
return INCLUDE_AND_CONTINUE;
})
]]></programlisting>
In the last part of this exercise we wanted to add recommendations to the app. One obvious recommendation is
movies that our friends liked
(and their friends too, but with less importance). The second was recommendations for new friends that also
liked the movies that we liked most.
</para>
<para>
Doing this kind of ranking algorithms is really fun with graph databases. They are applied to the graph by
traversing it in a certain order, collecting information on the go and deciding which paths to follow and what
to include in the results.
</para>
<para>
Lets say we're only interested in the recommendations of a certain degree of friends.
</para>
<para>
<programlisting language="java"><![CDATA[
public Map<Movie,Integer> recommendMovies(User user, final int ratingDistance) {
final DynamicRelationshipType RATED = withName(User.RATED);
final Map<Long,int[]> ratings=new HashMap<Long, int[]>();
TraversalDescription traversal= Traversal.description().breadthFirst()
.relationships(withName(User.FRIEND)).relationships(RATED, OUTGOING).evaluator(new Evaluator() {
public Evaluation evaluate(Path path) {
final int length = path.length() - 1;
if (length > ratingDistance) return Evaluation.EXCLUDE_AND_PRUNE; // only as far as requested
Relationship rating = path.lastRelationship();
if (rating != null && rating.getType().equals(RATED)) { // process RATED relationships, not FRIEND
if (length == 0) return Evaluation.EXCLUDE_AND_PRUNE; // my rated movies
final long movieId = rating.getEndNode().getId();
int[] stars = ratings.get(movieId);
if (stars == null) {
stars = new int[2];
ratings.put(movieId, stars);
}
int weight = ratingDistance - length; // aggregate for averaging, inverse to distance
stars[0] += weight * (Integer) rating.getProperty("stars", 0);
stars[1] += weight;
return Evaluation.INCLUDE_AND_PRUNE;
}
return Evaluation.EXCLUDE_AND_CONTINUE;
}
});
Map<Movie,Integer> result=new HashMap<Movie, Integer>();
final Iterable<Movie> movies = movieRepository.findAllByTraversal(user, traversal); // lazy traversal results
for (Movie movie : movies) { // assign movie to averaged rating
final int[] stars = ratings.get(movie.getNodeId());
result.put(movie, stars[0]/stars[1]);
}
return result;
}
]]></programlisting>
</para>
<para>
The UserController just calls this method, adds it's results to the the model and the view renders the
recommendation alongside with your own ratings.
</para>
</chapter>