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 <[email protected]>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: [email protected] > 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> > ------------------------------------------------------------ > -------------------------------------- >
