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href="#modification">Modification</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/ecommercerecommendation/adjust-score.html.md.erb";><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">PredictionIO Official Templates</a><span class="spacer">></span></li><li><a href="#">E-Commerce Recommendation</a><span class="spacer">></span></li><li><span class="last">Adjust Score</span></li></ul></div><div id="page-title"><h1>Adjust Score (E-Commerce Recommendation)</h1></div></div><div class="content"> <p>This examples demonstra tes how to modify E-Commerce Recommendation template to further adjust score.</p><p>By default, items have a weight of 1.0. Giving an item a weight greater than 1.0 will make them appear more often and can be useful for i.e. promoted products. An item can also be given a weight smaller than 1.0 (but bigger than 0), in which case it will be recommended less often than originally. Weight values smaller than 0.0 are invalid.</p><p>You can find the complete modified source code <a href="https://github.com/apache/incubator-predictionio/tree/develop/examples/scala-parallel-ecommercerecommendation/adjust-score";>here</a>.</p><h2 id='modification' class='header-anchors'>Modification</h2><h3 id='ecommalgorithm.scala' class='header-anchors'>ECommAlgorithm.scala</h3><p>Add a case class to represent each group items which are given the same weight.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +2 +3 +4 +5</pre></td><td class="code"><pre><span class="c1">// ADDED +</span><span class="k">case</span> <span class="k">class</span> <span class="nc">WeightGroup</span><span class="o">(</span> + <span class="n">items</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span> + <span class="n">weight</span><span class="k">:</span> <span class="kt">Double</span> +<span class="o">)</span> +</pre></td></tr></tbody></table> </div> <p>In ECommAlgorithm, add <code>weightedItems</code> function to extract the sequence of <code>WeightGroup</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +2 +3 +4 +5 +6 +7 +8 +9 +10 +11 +12 +13 +14 +15 +16 +17 +18 +19 +20 +21 +22 +23 +24 +25 +26 +27 +28</pre></td><td class="code"><pre> <span class="c1">// ADDED +</span> <span class="cm">/** Get the latest constraint weightedItems */</span> + <span class="k">def</span> <span class="n">weightedItems</span><span class="k">:</span> <span class="kt">Seq</span><span class="o">[</span><span class="kt">WeightGroup</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span> + <span class="k">try</span> <span class="o">{</span> + <span class="k">val</span> <span class="n">constr</span> <span class="k">=</span> <span class="nc">LEventStore</span><span class="o">.</span><span class="n">findByEntity</span><span class="o">(</span> + <span class="n">appName</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span> + <span class="n">entityType</span> <span class="k">=</span> <span class="s">"constraint"</span><span class="o">,</span> + <span class="n">entityId</span> <span class="k">=</span> <span class="s">"weightedItems"</span><span class="o">,</span> + <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Seq</span><span class="o">(</span><span class="s">"$set"</span><span class="o">)),</span> + <span class="n">limit</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">1</span><span class="o">),</span> + <span class="n">latest</span> <span class="k">=</span> <span class="kc">true</span><span class="o">,</span> + <span class="n">timeout</span> <span class="k">=</span> <span class="nc">Duration</span><span class="o">(</span><span class="mi">200</span><span class="o">,</span> <span class="s">"millis"</span><span class="o">)</span> + <span class="o">)</span> + <span class="k">if</span> <span class="o">(</span><span class="n">constr</span><span class="o">.</span><span class="n">hasNext</span><span class="o">)</span> <span class="o">{</span> + <span class="n">constr</span><span class="o">.</span><span class="n">next</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Seq</span><span class="o">[</span><span class="kt">WeightGroup</span><span class="o">]](</span><span class="s">"weights"</span><span class="o">)</span> + <span class="o">}</span> <span class="k">else</span> <span class="o">{</span> + <span class="nc">Nil</span> + <span class="o">}</span> + <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span> + <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">scala.concurrent.TimeoutException</span> <span class="o">=></span> + <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Timeout when read set weightedItems event."</span> <span class="o">+</span> + <span class="n">s</span><span class="s">" Empty list is used. ${e}"</span><span class="o">)</span> + <span class="nc">Nil</span> + <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> + <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Error when read set weightedItems event: ${e}"</span><span class="o">)</span> + <span class="k">throw</span> <span class="n">e</span> + <span class="o">}</span> + <span class="o">}</span> +</pre></td></tr></tbody></table> </div> <p>Modify the <code>predictKnownUser()</code>, <code>predictDefault()</code> and <code>predictSimilar()</code>:</p> <ul> <li>add the <code>weights: Map[Int, Double]</code> parameter</li> <li>adjust score according to item weights</li> </ul> <div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +2 +3 +4 +5 +6 +7 +8 +9 +10 +11 +12 +13 +14 +15 +16 +17 +18 +19 +20 +21</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">predictKnownUser</span><span class="o">(</span> + <span class="n">userFeature</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">],</span> + <span class="n">productModels</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">ProductModel</span><span class="o">],</span> + <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span> + <span class="n">whiteList</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">Int</span><span class="o">]],</span> + <span class="n">blackList</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">Int</span><span class="o">],</span> + <span class="n">weights</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">Double</span><span class="o">]</span> <span class="c1">// ADDED +</span> <span class="o">)</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[(</span><span class="kt">Int</span>, <span class="kt">Double</span><span class="o">)]</span> <span class="k">=</span> <span class="o">{</span> + + <span class="o">...</span> + <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">i</span><span class="o">,</span> <span class="n">pm</span><span class="o">)</span> <span class="k">=></span> + <span class="c1">// NOTE: features must be defined, so can call .get +</span> <span class="k">val</span> <span class="n">s</span> <span class="k">=</span> <span class="n">dotProduct</span><span class="o">(</span><span class="n">userFeature</span><span class="o">,</span> <span class="n">pm</span><span class="o">.</span><span class="n">features</span><span class="o">.</span><span class="n">get</span><span class="o">)</span> + <span class="c1">// may customize here to further adjust score +</span> <span class="c1">// ADDED +</span> <span class="k">val</span> <span class="n">adjustedScore</span> <span class="k">=</span> <span class="n">s</span> <span class="o">*</span> <span class="n">weights</span><span class="o">(</span><span class="n">i</span><span class="o">)</span> + <span class="o">(</span><span class="n">i</span><span class="o">,</span> <span class="n">adjustedScore</span><span class="o">)</span> + <span class="o">}</span> + <span class="o">...</span> + + <span class="o">}</span> +</pre></td></tr></tbody></table> </div> <p>Lastly, modify the <code>predict()</code> method. The sequence of <code>WeightGroup</code> transforms into a <code>Map[Int, Double]</code> that we can easily query to extract the weight given to an item, using its <code>Int</code> index.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +2 +3 +4 +5 +6 +7 +8 +9 +10 +11 +12 +13 +14 +15 +16 +17 +18 +19 +20 +21 +22 +23 +24 +25 +26 +27 +28 +29 +30 +31 +32 +33 +34 +35 +36 +37 +38 +39 +40 +41 +42 +43 +44 +45 +46 +47 +48 +49 +50 +51</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">model</span><span class="k">:</span> <span class="kt">ECommModel</span><span class="o">,</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span> + + <span class="o">...</span> + + <span class="c1">// ADDED +</span> <span class="k">val</span> <span class="n">weights</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="o">(</span><span class="k">for</span> <span class="o">{</span> + <span class="n">group</span> <span class="k"><-</span> <span class="n">weightedItems</span> + <span class="n">item</span> <span class="k"><-</span> <span class="n">group</span><span class="o">.</span><span class="n">items</span> + <span class="n">index</span> <span class="k"><-</span> <span class="n">model</span><span class="o">.</span><span class="n">itemStringIntMap</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">item</span><span class="o">)</span> + <span class="o">}</span> <span class="k">yield</span> <span class="o">(</span><span class="n">index</span><span class="o">,</span> <span class="n">group</span><span class="o">.</span><span class="n">weight</span><span class="o">))</span> + <span class="o">.</span><span class="n">toMap</span> + <span class="o">.</span><span class="n">withDefaultValue</span><span class="o">(</span><span class="mf">1.0</span><span class="o">)</span> + + <span class="o">...</span> + + <span class="k">val</span> <span class="n">topScores</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[(</span><span class="kt">Int</span>, <span class="kt">Double</span><span class="o">)]</span> <span class="k">=</span> <span class="k">if</span> <span class="o">(</span><span class="n">userFeature</span><span class="o">.</span><span class="n">isDefined</span><span class="o">)</span> <span class="o">{</span> + <span class="c1">// the user has feature vector +</span> <span class="n">predictKnownUser</span><span class="o">(</span> + <span class="n">userFeature</span> <span class="k">=</span> <span class="n">userFeature</span><span class="o">.</span><span class="n">get</span><span class="o">,</span> + <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span> + <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span> + <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span> + <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span><span class="o">,</span> + <span class="n">weights</span> <span class="k">=</span> <span class="n">weights</span> <span class="c1">// ADDED +</span> <span class="o">)</span> + <span class="o">}</span> <span class="k">else</span> <span class="o">{</span> + <span class="o">...</span> + + <span class="k">if</span> <span class="o">(</span><span class="n">recentFeatures</span><span class="o">.</span><span class="n">isEmpty</span><span class="o">)</span> <span class="o">{</span> + <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">"No features vector for recent items ${recentItems}."</span><span class="o">)</span> + <span class="n">predictDefault</span><span class="o">(</span> + <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span> + <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span> + <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span> + <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span><span class="o">,</span> + <span class="n">weights</span> <span class="k">=</span> <span class="n">weights</span> <span class="c1">// ADDED +</span> <span class="o">)</span> + <span class="o">}</span> <span class="k">else</span> <span class="o">{</span> + <span class="n">predictSimilar</span><span class="o">(</span> + <span class="n">recentFeatures</span> <span class="k">=</span> <span class="n">recentFeatures</span><span class="o">,</span> + <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span> + <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span> + <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span> + <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span><span class="o">,</span> + <span class="n">weights</span> <span class="k">=</span> <span class="n">weights</span> <span class="c1">// ADDED +</span> <span class="o">)</span> + <span class="o">}</span> + <span class="o">}</span> + + <span class="o">...</span> + <span class="o">}</span> +</pre></td></tr></tbody></table> </div> <p>Now, to send an event to Event Server:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +2 +3 +4 +5 +6 +7 +8 +9 +10 +11 +12 +13 +14 +15 +16 +17 +18 +19 +20</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span> +-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span> +-d <span class="s1">'{ + "event" : "$set", + "entityType" : "constraint", + "entityId" : "weightedItems", + "properties" : { + "weights": [ + { + "items": ["i4", "i14"], + "weight": 1.2 + }, + { + "items": ["i11"], + "weight": 1.5 + } + ] + }, + "eventTime" : "2014-11-02T09:39:45.618-08:00" +}'</span> +</pre></td></tr></tbody></table> </div> <p>That's it! Now your engine can predict with adjusted scores.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//predictionio.incubator.apache.org/install/" target="blank">Download</a></li><li><a href="//predictionio.incubator.apache.org/" target="blank">Docs</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">GitHub</a></li><li><a href="mailto:[email protected]"; target="blank">Subscribe to User Mailing List</a></li><li><a href="//stackoverflow.com/questions/tagged/predictionio" target="blank">Stackoverflow</a></li></ul></div></div><div class="col-md-6 footer-link-column"><div class="footer-link-column-row"><h4>Contribute</h4><ul><li><a href="//predictionio.incubator.apache.org/community/contribute-code/" target="bl ank">Contribute</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">Source Code</a></li><li><a href="//issues.apache.org/jira/browse/PIO" target="blank">Bug Tracker</a></li><li><a href="mailto:[email protected]"; target="blank">Subscribe to Development Mailing List</a></li></ul></div></div></div><div class="row"><div class="col-md-12 footer-link-column"><a class="pull-right" href="http://incubator.apache.org/projects/predictionio.html";><img alt="Apache Incubator" src="/images/logos/apache_incubator-6954bd16.png"/></a><span>Apache PredictionIO is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. 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