Merge branch 'ctcvr_rank_model_833_v3' of algorithm/ad-engine into master

ad-engine-service/src/main/java/com/tzld/piaoquan/ad/engine/service/score/strategy/RankStrategyBy833.java

@@ -344,6 +344,15 @@ public class RankStrategyBy833 extends RankStrategyBasic {
                 .map(f -> f.get("layer"))
                 .map(s -> s.replace("-炸", ""))
                 .orElse(null);
+
+        // 控制曝光参数
+        String expOldKey = paramsMap.getOrDefault("expOldKey", "ad_view_yesterday");
+        double expOldThreshold = NumberUtils.toDouble(paramsMap.getOrDefault("expOldThreshold", "1000"));
+        String expNewKey = paramsMap.getOrDefault("expNewKey", "ad_view_today");
+        double expNewThreshold = NumberUtils.toDouble(paramsMap.getOrDefault("expNewThreshold", "3000"));
+        double expLowerWeight = NumberUtils.toDouble(paramsMap.getOrDefault("expLowerWeight", "0.2"));
+        double expUpperWeight = NumberUtils.toDouble(paramsMap.getOrDefault("expUpperWeight", "1.0"));
+        double expScale = NumberUtils.toDouble(paramsMap.getOrDefault("expScale", "10.0"));
         for (AdRankItem item : result) {
             double bid = item.getCpa();
             if (scoreParam.getExpCodeSet().contains(correctCpaExp1) || scoreParam.getExpCodeSet().contains(correctCpaExp2)) {
@@ -356,12 +365,20 @@ public class RankStrategyBy833 extends RankStrategyBasic {
                 isGuaranteeType = true;
             }
 
+            // 控制曝光权重
+            Map<String, Map<String, String>> cidFeature = allCidFeature.getOrDefault(String.valueOf(item.getAdId()), EMPTY_NESTED_MAP);
+            Map<String, String> b3Feature = cidFeature.getOrDefault("alg_cid_feature_cid_action", EMPTY_STRING_MAP);
+            double expWeight = getExpWeight(b3Feature,
+                    expOldKey, expOldThreshold,
+                    expNewKey, expNewThreshold,
+                    expLowerWeight, expUpperWeight, expScale);
+
             String layerAndCreativeWeightMapKey = getLayerAndCreativeWeightMapKey(peopleLayer, String.valueOf(item.getAdId()));
             // 人群分层&创意的权重
             double layerAndCreativeWeight = getLayerAndCreativeWeight(layerAndCreativeWeightMapKey);
             double scoreCoefficient = creativeScoreCoefficient.getOrDefault(item.getAdId(), 1d);
             double guaranteeScoreCoefficient = getGuaranteeScoreCoefficient(isGuaranteedFlow, item.getExt());
-            double score = item.getLrScore() * bid * scoreCoefficient * guaranteeScoreCoefficient * layerAndCreativeWeight;
+            double score = expWeight * item.getLrScore() * bid * scoreCoefficient * guaranteeScoreCoefficient * layerAndCreativeWeight;
             item.getScoreMap().put("guaranteeScoreCoefficient", guaranteeScoreCoefficient);
             item.getScoreMap().put("cpa", item.getCpa());
             item.getScoreMap().put("cpm", item.getCpm());
@@ -936,4 +953,30 @@ public class RankStrategyBy833 extends RankStrategyBasic {
         }
         return newFeatureMap;
     }
+
+    private double getExpWeight(Map<String, String> featureMap,
+                                String expOldKey, double expOldThreshold,
+                                String expNewKey, double expNewThreshold,
+                                double expLowerWeight, double expUpperWeight, double expScale) {
+        try {
+            if (null != featureMap) {
+                double oldView = Double.parseDouble(featureMap.getOrDefault(expOldKey, "0"));
+                if (oldView < expOldThreshold) {
+                    double newView = Double.parseDouble(featureMap.getOrDefault(expNewKey, "0"));
+                    return getExpWeight(expLowerWeight, expUpperWeight, expScale, expNewThreshold, newView);
+                }
+            }
+        } catch (Exception e) {
+            log.error("getExpWeight error: ", e);
+        }
+        return 1.0;
+    }
+
+    private double getExpWeight(double lowerWeight, double upperWeight, double scale, double upperExp, double exp) {
+        if (exp >= upperExp) {
+            return 1.0;
+        }
+        double weight = Math.log(exp + 1) / scale;
+        return Math.min(Math.max(lowerWeight, weight), upperWeight);
+    }
 }