LibRec - A Java Library for Recommender Systems

A Java Library for Recommender Systems. Recommender systems have been well recognized as a typical application of Big Data and Machine Learning. LibRec is a GPL-licensed Java library Java version 1.7 required, aiming to solve two classic problems in recommender systems, i.e., rating prediction. By implementing a suite of state-of-the-art recommendation algorithms. It has been listed by the RecSys Wiki see the LibRec page. A number of papers adopting LibRec can be found here. G Guo, J. Zhang and N.

OVERVIEW

This web site librec.net presently has an average traffic ranking of zero (the smaller the higher page views). We have explored zero pages inside the web page librec.net and found five websites linking to librec.net.
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5

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WHAT DOES LIBREC.NET LOOK LIKE?

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LIBREC.NET HOST

Our parsers found that a single page on librec.net took one thousand five hundred milliseconds to download. We could not detect a SSL certificate, so I consider librec.net not secure.
Load time
1.5 secs
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Internet Protocol
23.229.209.226

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SERVER OS AND ENCODING

I found that librec.net is using the Apache/2.4.23 server.

PAGE TITLE

LibRec - A Java Library for Recommender Systems

DESCRIPTION

A Java Library for Recommender Systems. Recommender systems have been well recognized as a typical application of Big Data and Machine Learning. LibRec is a GPL-licensed Java library Java version 1.7 required, aiming to solve two classic problems in recommender systems, i.e., rating prediction. By implementing a suite of state-of-the-art recommendation algorithms. It has been listed by the RecSys Wiki see the LibRec page. A number of papers adopting LibRec can be found here. G Guo, J. Zhang and N.

CONTENT

This web site has the following on the homepage, "A Java Library for Recommender Systems." We saw that the web site also said " Recommender systems have been well recognized as a typical application of Big Data and Machine Learning." It also said " LibRec is a GPL-licensed Java library Java version 1. 7 required, aiming to solve two classic problems in recommender systems, i. By implementing a suite of state-of-the-art recommendation algorithms. It has been listed by the RecSys Wiki see the LibRec page. A number of papers adopting LibRec can be found here."

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