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filmaster

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  No analysis available

Filmaster (now in public beta mode and available under filmaster.com) is a new social network for movie fans, with personalized content and recomendations. And all that free as in beer and as in speech. Filmaster allows you to run your own film blog in a great domain like you.filmaster.com, rate ... [More] movies and talk about movies with people whose opinions you care about. Personalized recommendations are a bonus. Filmaster is being developed as an open source project (using django framework) and everyone is welcome to participate! [Less]

0 lines of code

0 current contributors

0 since last commit

4 users on Open Hub

Activity Not Available
5.0
 
I Use This
Mostly written in language not available
Licenses: AGPL3_or_...

Taste

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  Analyzed 34 minutes ago

Taste is a flexible, fast collaborative filtering engine for Java. It has been merged into Apache's Mahout machine learning project since 2009. See http://mahout.apache.org

11.7K lines of code

0 current contributors

over 17 years since last commit

3 users on Open Hub

Inactive
5.0
 
I Use This

Crab - Scikit-Recommender

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  Analyzed 1 day ago

Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (NumPy,SciPy, Matplotlib). The engine aims to provide a rich set of components from which you can construct a customized ... [More] recommender system from a set of algorithms. It is designed for scability, flexibility and performance making use of scientific optimized python packages in order to provide simple and efficient solutions that are acessible to everybody and reusable in various contexts: science and engineering. [Less]

4.21K lines of code

0 current contributors

almost 14 years since last commit

2 users on Open Hub

Inactive
5.0
 
I Use This

cm-context-related-product-recommendations

  Analyzed 1 day ago

The Context Related Product Recommendations Plugin intelligently displays product suggestions based on the content users are browsing. By offering relevant, context-driven recommendations, it enhances user experience, increases engagement, and helps boost sales with personalized product suggestions.

14.8K lines of code

0 current contributors

10 months since last commit

0 users on Open Hub

Very Low Activity
0.0
 
I Use This