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通过Mahout构建推荐系统时,如果我们需要加入某些过滤规则(比如:item的创建时间在一年以内),则需要用到
IDRescorer 接口,该接口源码如下: package org.apache.mahout.cf.taste.recommender; * A {@link Rescorer} which operates on {@code long} primitive IDs, rather than arbitrary {@link Object}s. * This is provided since most uses of this interface in the framework take IDs (as {@code long}) as an * argument, and so this can be used to avoid unnecessary boxing/unboxing. public interface IDRescorer { * ID of thing (user, item, etc.) to rescore * @return modified score, or {@link Double#NaN} to indicate that this should be excluded entirely double rescore(long id, double originalScore); * Returns {@code true} to exclude the given thing. * ID of thing (user, item, etc.) to rescore * @return {@code true} to exclude, {@code false} otherwise boolean isFiltered(long id); 功能:定义重新评分的逻辑。根据新的规则,为指定id的item重新评分。 功能:定义过滤规则。判断指定id的item,根据新的规则,是否该排除在外,返回true就是该item应该排除在结果之外。
无论是否需要根据特定规则过滤推荐结果,都必须先创建
org.apache.mahout.cf.taste.recommender.Recommender类的对象r,然后通过对象r来执行推荐方法获得针对特定id用户的推荐结果List。 当无需使用特定规则过滤推荐结果时,只需使用
Recommender对象的如下方法获得推荐结果 : * user for which recommendations are to be computed * desired number of recommendations * @return {@link List} of recommended {@link RecommendedItem}s, ordered from most strongly recommend to * if an error occurs while accessing the {@link DataModel} List<RecommendedItem> recommend(long userID, int howMany) throws TasteException; 当需要根据特定规则过滤推荐结果时,需使用
Recommender对象的如下方法获得推荐结果 : * user for which recommendations are to be computed * desired number of recommendations * rescoring function to apply before final list of recommendations is determined * @return {@link List} of recommended {@link RecommendedItem}s, ordered from most strongly recommend to * if an error occurs while accessing the {@link DataModel} List<RecommendedItem> recommend(long userID, int howMany, IDRescorer rescorer) throws TasteException; 其中,最后一个参数就是本文开始提到的 IDRescorer。 所以,当需要通过特定规则过滤推荐结果时,需先实现IDRescorer接口,定义评分逻辑和排除规则。