I looked at the docs and the AGPL for the server is a problem for me—maybe even a blocker. Since the SDK is useless without the server, this may be a problem for you.
I like the SDK, idea. The alternative is logfiles to store prefs (not a bad architecture really) and a grow your own method for getting recs. I did this same thing in Ruby+REST for a site and it might save a fair bit of work if you support the usual web app frameworks. The SDK for storing prefs makes even more sense if you have realtime use of them. Unless you did something fancy with Mahout under the covers they will only take affect when the model is recalculated. It looks like you have a scheduler too as an answer to the new model issue. Pretty nice and a good example for people rolling their own. The UI is interesting but I wonder how many recommenders any one user is going to create. I imagine you have in mind doing this as a service and that’s why you have the UI and AGPL. On Mar 19, 2014, at 4:35 AM, Piero Giacomelli <pgiac...@gmail.com> wrote: 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> --------------------------------------------------------------------------------------------------
