Actually the spark-itemsimilarity job and related code in the Spark module of Mahout creates all-pairs similarity too. It’s designed to use with a search engine, which provides the query part of the recommender. Integrate the two and you have a near realtime scalable item-based/cooccurrence collaborative filtering type recommender.
On Nov 30, 2014, at 12:09 PM, Sean Owen <so...@cloudera.com> wrote: There is an implementation of all-pairs similarity. Have a look at the DIMSUM implementation in RowMatrix. It is an element of what you would need for such a recommender, but not the whole thing. You can also do the model-building part of an ALS-based recommender with ALS in MLlib. So, no not directly, but there are related pieces. On Sun, Nov 30, 2014 at 5:36 PM, shahab <shahab.mok...@gmail.com> wrote: > Hi, > > I just wonder if there is any implementation for Item-based Collaborative > Filtering in Spark? > > best, > /Shahab --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
