Recommendation Systems lies above Information Retrieval and is used by e-commerce, electronic ads, and news websites to deliver valuable data, helping users decide what can be useful for them. For the next years, the big amount of data generated every day is becoming increasingly difficult to be processed, and find relevant information requires specialized algorithms.
These challenges motivated us, in continuing a former academic work. In the beginning of 2014, we restarted the project by reviewing what was done so far.
After reviewing everything, all algorithms were optimized and splitted into 3 APIs: Core, Tag Recommendation and Content Recommendation.
Those APIs are available in the Resources section, or directly through this link.
Our research is evolutionary, so the content of the website will be always updated, once our results analysis is finished, they will be published.
We think that knowledge is best enjoyed when it's shared with the community.
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