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Neo4j Based Recommendation Engine Module with real-time and pre-computed recommendations.
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/*
* Copyright (c) 2013-2020 GraphAware
*
* This file is part of the GraphAware Framework.
*
* GraphAware Framework is free software: you can redistribute it and/or modify it under the terms of
* the GNU General Public License as published by the Free Software Foundation, either
* version 3 of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
* See the GNU General Public License for more details. You should have received a copy of
* the GNU General Public License along with this program. If not, see
* {
private final NodeSelector selector;
public RandomRecommendations() {
this.selector = new RandomNodeSelector(getPolicy());
}
/**
* {@inheritDoc}
*/
@Override
public ParticipationPolicy participationPolicy(Context context) {
//noinspection unchecked
return ParticipationPolicy.IF_MORE_RESULTS_NEEDED;
}
/**
* {@inheritDoc}
*
* A maximum of {@link Context#config()} {@link Config#limit()} number of nodes is returned, each with
* a score determined by {@link #score(org.neo4j.graphdb.Node)}. The total number of attempts made to find a suitable
* node is determined by {@link #numberOfAttempts(com.graphaware.reco.generic.context.Context)}.
*/
@Override
protected final Map doRecommendSingle(Node input, Context context) {
Map result = new HashMap<>();
int attempts = 0;
int numberOfAttempts = numberOfAttempts(context);
int numberOfRecommendations = numberOfRecommendations(context);
while (attempts++ < numberOfAttempts && result.size() < numberOfRecommendations) {
Node node = selector.selectNode(input.getGraphDatabase());
if (node != null) {
result.put(node, score(node));
}
}
return result;
}
/**
* Score a randomly selected node.
*
* @param node to score.
* @return score, 0 by default.
*/
protected PartialScore score(Node node) {
return new PartialScore();
}
/**
* Determine the maximum total number of attempts to make when selecting random nodes to recommend.
*
* @param context of the current computation.
* @return maximum number of attempts. By default 10 * {@link Context#config()} {@link Config#limit()}
*/
protected int numberOfAttempts(Context context) {
return context.config().limit() * 10;
}
/**
* Determine the maximum number of random nodes to recommend.
*
* The reason for this setting is the following: usually, this engine will be used as the last one to make up the
* desired number of recommendations. If only {@link Context#config()} {@link Config#limit()} recommendations
* were produced, there could be a possibility that the produced recommendations are the ones already computed by
* previous engines, thus not making up the desired number. The higher the return value of this method, the lower
* the chance of the desired number of recommendations not being satisfied.
*
* @param context of the current computation.
* @return maximum number of recommendations. By default 2 * {@link Context#config()} {@link Config#limit()}
*/
protected int numberOfRecommendations(Context context) {
return context.config().limit() * 2;
}
/**
* Get the node inclusion policy of the nodes that can be used as recommendations.
*
* @return policy.
*/
protected abstract NodeInclusionPolicy getPolicy();
}