This project contains a Webserver with Apache Mahout as recommender engine, to provide recommendations using the collaborative filtering technique. The webserver is build up with the Spring Framework. All recommendations and further features can be accessed via a webservice-interface. Additionally there is a web front-end, for an quick and easy access to the webserver.
recommender-console's Introduction
recommender-console's People
recommender-console's Issues
get k of kNN automatically?
JMeter Load test
Evaluate load on recommendations server
Hama Data Transformation
Transform tracking data to preferences
set neighborhood threshold
get 10M file to run
long to String and vice versa
Implement Client for Servers (as jar lib)
RecommenderCeption
error handling
catch error, show errors on page
Rendering too many Users ( like 70.000) is creating overhead
Also holding users as Objects in server -> consuming memory
exponential growth of memory
1mil --> ca. 400-500mb
10mil --> ca. 50gb!!
Implement Mahout Evaluator for Recommenders
compare MySQL and csv data loading time with 10mil preferences
Try to use MapReduce for transforming data
ReloadFromJDBCDataModel
Integrate recommendations to jStage demo shop
chose neighborhood setting for user-baed
find correlation between number of preferences and computation time of recommendations for this user
Precompute item similarities to boost them up!
recommendedBecause can not be created using caching decorater!!
Add Caching decorater to Recommenders!
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