text mining

CORE’s open access and text mining services – 2016 growth (or, how about them stats – 2016 edition)

The past year has been productive for the CORE team; the number of harvested repositories and our open access content, both in metadata and full-text, has massively increased. (You can see last year’s blog post with our 2015 achievements in numbers here.)

There was also progress with regards to our services; the number of our API users was almost doubled in 2016, we have now about 200 registered CORE Dashboard users, and this past October we released a new version of our recommender and updated our dataset. read more...

CORE released a new Dataset

We are pleased to announce that we have released a new version of our dataset, which contains data aggregated by CORE in a downloadable file.

It is intended for (possibly computationally intensive) data analysis. Here you can read the dataset description and the download page. If you need fresh data, and your requirements are not computationally intensive, you can also use our API.

CORE Recommender

* This post was authored by Nancy Pontika, Lucas Anastasiou and Petr Knoth.

The CORE team is thrilled to announce the release of a new version of our recommender; a plugin that can be installed in repositories and journal systems to suggest similar articles. This is a great opportunity to improve the functionality of repositories by unleashing the power of recommendation over a huge collection of open-access documents, currently 37 million metadata records and more than 4 million full-text, available in CORE. read more...