Dear Bertrand
Yes, that was what I understood.
But for me I miss a step.
Let us take a practical example.
I use SlopeRecommender engine and I implement its policy on how to
evaluate the similarity.
In this case I made a custom version on the engine right?
The SKD is not customize. So my question is should I give the custom
code to the client in chase he/she ask me.
Piero
Il 19/03/2014 11:56, Bertrand Dechoux ha scritto:
Affero GPL : http://en.wikipedia.org/wiki/Affero_General_Public_License
Alfresco is something else.
It does imply that if you provide someone access to a custom version of the
engine, then you must provide the sources. But is only about the engine ie
not the clients, not the configuration, not the data. An official
confirmation would be welcome.
Bertrand
On Wed, Mar 19, 2014 at 11:40 AM, Piero Giacomelli <pgiac...@gmail.com>wrote:
Dear Simon,
thanks for informing us.
I am now evaluating Prediction.io for creating a reccomandation system.
However as I see the license is an Alfresco Limited one.
So I do not understand what are the limitation.
I mean if I install prediction and I do make some chanages to the source
code should I redistribute the whole to the predicition.io developer team.
Piero
Il 18/03/2014 21:00, Simon Chan ha scritto:
Hi,
After a year of work, I would like to present PredictionIO project (
https://github.com/PredictionIO) to this community.
When a few of us were doing PhD study, Mahout was the de facto Java
package
that we used in many research work. This is a very powerful algorithm
library, yet we see that something needs to be done to make it more
accessible to developers in production environment.
Therefore, we started the idea of PredictionIO, which adds a
developer-friendly REST API, a web admin UI and an integrated
infrastructure on top of Mahout. The project is still at its early stage.
CF algorithm libraries of Mahout is supported currently.
*REST API and SDK* in Python, Ruby, Java, PHP, Node.js etc
Through the API layer, which supports both sync and asycn call, users can:
- Record data
A sample SDK call:
* cli.identify("John")*
* cli.record_action_on_item("view", "Mahout Page 1")*
- Query recommendation in real-time
A sample GEO-based recommendation query:
* r = cli.get_itemrec_topn("myEngine", 5, {"pio_latlng":[37.9, 91.2]})*
*Web Admin UI*
Through the UI, users can:
- conduct algorithm evaluation with metrics such as MAP@k
- deploy / switch algorithm on production
- adjust recommendation preferences, such as Freshness, Serendipity,
Unseen-only filter etc
*Integrated Infrastructure*
PredictionIO helps users link Mahout, Hadoop, data store and job scheduler
etc together. The whole stack can be installed and configured in minutes.
It takes care of a lot of production issues, such as model re-training
with
new data and prediction result indexing.
We are working hard to make it extremely easy for developers to build
Machine Learning into web and apps. Hopefully, PredictionIO can get Mahout
into the hands of a wider audience.
Love to hear your feedback. If you are interested in the project, just
remember that contributors are always welcome!
Regards,
Simon
--
Piero Giacomelli, Italia
phone:+39 34 71 02 42 95
e-mail: pgiac...@gmail.com
skype: pgiacome
my books
------------------------------------------------------------
--------------------------------------
Apache Mahout Cookbook <http://www.packtpub.com/
apache-mahout-cookbook/book>
HornetQ Messaging Developer's Guide <HornetQ%20Messaging%
20Developer%27s%20Guide>
------------------------------------------------------------
--------------------------------------
--
Piero Giacomelli, Italia
phone:+39 34 71 02 42 95
e-mail: pgiac...@gmail.com
skype: pgiacome
my books
--------------------------------------------------------------------------------------------------
Apache Mahout Cookbook <http://www.packtpub.com/apache-mahout-cookbook/book>
HornetQ Messaging Developer's Guide
<HornetQ%20Messaging%20Developer%27s%20Guide>
--------------------------------------------------------------------------------------------------
