Here is Item-based Recommender Example:
=====
public class ItemBasedRecommender implements Recommender {
private final Recommender recommender;
public ItemBasedRecommender() throws IOException, TasteException {
this(new MovieDataModel());
}
public ItemBasedRecommender(DataModel dataModel) throws TasteException {
Collection<GenericItemSimilarity.ItemItemSimilarity> correlations =
MovieSimilarityTable.getAllMovieSimilarities();
ItemSimilarity itemSimilarity = new
GenericItemSimilarity(correlations);
recommender = new CachingRecommender(new
EmbededItemBasedRecommender(
new GenericItemBasedRecommender(dataModel, itemSimilarity)));
}
public List<RecommendedItem> recommend(long userID, int howMany)
throws TasteException {
return recommender.recommend(userID, howMany);
}
.........
//EmbededItemBasedRecommender类的定义
private static final class EmbededItemBasedRecommender implements
Recommender {
//包含一个GenericItemBasedRecommender实例；
private final GenericItemBasedRecommender recommender;
private EmbededItemBasedRecommender(GenericItemBasedRecommender
recommender) {
this.recommender = recommender;
}
public List<RecommendedItem> recommend(long userID, int howMany,
Rescorer<Long> rescorer)
throws TasteException {
FastIDSet itemIDs =
recommender.getDataModel().getItemIDsFromUser(userID);
return recommender.mostSimilarItems(itemIDs.toArray(), howMany,
null);
}
........
}
======
The parameters of recommend method are userID and howMany,not include
itemID,so I think for one user and every item,the recommendations are same.
On Mon, Sep 20, 2010 at 11:34 PM, Sebastian Schelter <[email protected]> wrote:
> Sam,
>
> can you provide an example and a little more details about your data and
> the implementations you use?
>
> --sebastian
>
> Am 20.09.2010 17:28, schrieb Sam Yang:
> > All:
> > When I use Item-based recommender to do recommendation for user,but for
> each
> > item,the recommendations are same.
> > Is there some way to return different recommendations for different item?
> >
> > And,my story is when one user loggined, show recommendations on item
> detail
> > page,can these recommendations are different for each item?
> >
> >
>
>
--
I'm samsam.
