private IRecommendationEngine GetRecommendationEngine(CommerceDataSourceContext context, ParsedGenericCommerceDataSourceSettings settings, out ISet <string> toIgnoreItems)
{
var filter = settings.Filters.Find(f => f.Name == "ByProduct");
if (filter != null)
{
var productId = (int)filter.GetParameterValue("ProductId");
toIgnoreItems = new HashSet <string> {
productId.ToString()
};
return(new FeatureBasedRecommendationEngine(new[] { new Feature(productId.ToString()) }, RelatedItemsProviders.GetProviders(context.Instance)));
}
else
{
toIgnoreItems = new HashSet <string>();
foreach (var behaviorType in BehaviorTypes.All())
{
var store = BehaviorStores.Get(context.Instance, behaviorType);
foreach (var itemId in store.GetItemsUserHadBehaviorsOn(context.HttpContext.EnsureVisitorUniqueId(), 10000))
{
toIgnoreItems.Add(itemId);
}
}
return(RecommendationEngines.GetEngines(context.Instance));
}
}
public void Execute(JobContext context)
{
var instance = context.Instance;
var behaviorType = context.JobData["BehaviorType"];
var matrix = SimilarityMatrixes.Get(instance, behaviorType);
var newMatrix = matrix.PrepareRecomputation();
Recompute(newMatrix, BehaviorStores.Get(instance, behaviorType));
matrix.ReplaceWith(newMatrix);
}
static WeightedRecommendationEngineCollection CreateRecommendationEngines(string instance)
{
var engines = new WeightedRecommendationEngineCollection();
foreach (var behaviorType in BehaviorTypes.All())
{
var featureBuilder = new BehaviorBasedFeatureBuilder(() =>
{
var store = BehaviorStores.Get(instance, behaviorType);
return(store.GetRecentBehaviors(50));
});
var engine = new FeatureBasedRecommendationEngine(featureBuilder, RelatedItemsProviders.GetProviders(instance));
engines.Add(engine, 1f);
}
return(engines);
}
