问题导读
1.IDRescorer接口规定了哪些个必须实现的方法?
2.如何定义过滤规则?
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);
-
- }
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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:
file:///C:/Users/ADMINI~1/AppData/Local/Temp/Wiz/111206981.png
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:
file:///C:/Users/ADMINI~1/AppData/Local/Temp/Wiz/111244609.png
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;
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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}
- */
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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。
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