lenskit recommend - recommend items for users.


lenskit [GLOBAL OPTIONS] global-recommend [OPTIONS] ITEM


The global-recommend command recommends items based on some reference items (e.g. a shopping basket). It loads a recommender from a trained model file and/or LensKit configuration scripts and uses the configured algorithm to produce recommendations.


One or more items to use as a reference.
Show usage help.
-n N
Produce N recommendations. The default is 10.
-m FILE, –model-file FILE
Load a trained recommender engine from FILE.
-c SCRIPT, –config-file SCRIPT
Configure the recommender using SCRIPT. This option can be specified multiple times, and later configurations take precedence over earlier ones. If --model-file is also specified, the scripts are used to modify the trained model.
–print-channel CHAN
In addition to item scores, also print the value in side channel CHAN.

This command also takes the standard input data options and script environment options.

See Also

lenskit(1), lenskit-input-data(7), lenskit-script-environment(7)

Project Information

This command is a part of LensKit, an open source recommender systems toolkit developed by GroupLens Research. Copyright 2010-2014 Regents of the University of Minnesota and contributors.

Work on LensKit has been funded by the National Science Foundation under grants IIS 05-34939, 08-08692, 08-12148, and 10-17697.

This program is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.