Thanks.
Do you know of any fast way to obtain document-document similarity in Lucene
and write it to a text Mahout can read?
Ah, while playing a bit with item based recommenders I found a bug in
MySQLJDBCDataModel
// getNumPreferenceForItemsSQL
"SELECT COUNT(1) FROM " + preferenceTable + " tp1 INNER JOIN " +
preferenceColumn + " tp2 " +
"ON (tp1." + userIDColumn + "=tp2." + userIDColumn + ") " +
"WHERE tp1." + itemIDColumn + "=? and tp2." + itemIDColumn + "=?");
It should be
"SELECT COUNT(1) FROM " + preferenceTable + " tp1 INNER JOIN " +
preferenceTable....
-----Messaggio originale-----
Da: Sean Owen [mailto:[email protected]]
Inviato: giovedì 23 luglio 2009 20.51
A: [email protected]
Oggetto: Re: Using Item Based recommenders as content based recommenders
Yes, this is entirely reasonable.
You could also proceed by pre-computing user-user similarities and
using a user-based recommender. While it seems very much the same, I
wouldn't do that actually. Pre-computing kind of relies on the
assumption that similarities won't change much as you learn more, and
that is far more true of docs than users.
