【甘道夫】通过Mahout构建推荐系统--通过IDRescorer扩展评分规则
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;
/**
* <p>
* 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.
* </p>
*/
public interface IDRescorer {
/**
* @param id
* ID of thing (user, item, etc.) to rescore
* @param originalScore
* original score
* @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.
*
* @param id
* ID of thing (user, item, etc.) to rescore
* @return {@code true} to exclude, {@code false} otherwise
*/
boolean isFiltered(long id);
}
该接口规定了两个必须实现的方法：
1.rescore方法
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。
返回：重评后的分数
输入参数：item的id，该item原来的评分
调用该方法的方法包括：
2.isFiltered
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。
返回：true or false
输入参数：指定的id
调用该方法的方法包括：
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
：
/**
* @param userID
* user for which recommendations are to be computed
* @param howMany
* desired number of recommendations
* @return {@link List} of recommended {@link RecommendedItem}s, ordered from most strongly recommend to
* least
* @throws TasteException
* 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
：
/**
* @param userID
* user for which recommendations are to be computed
* @param howMany
* desired number of recommendations
* @param rescorer
* 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
* least
* @throws TasteException
* 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。