Resources on TDM:
Myths and Misunderstandings about Text and Data Mining in the Copyright Reform
In this document, we are busting myths that exist around TDM in the copyright reform
Text and Data Mining in the context of Smart Data
Patrick Bunk, CEO and Founder of Ubermetrics drafted an op-ed looking at the economics of Text and Data Mining and how a limited exception could harm the development of an ecosystem of European companies working on smart data and developing artificial intelligence.
ScienceEurope's full report on TDM
The importance of Content Mining for Science
Copyright Law may drive successful startups out of Europe
Founder Michal Brzezicki talks about the impact of the copyright reform on Polish startup SentiOne, a social listening tool, which conducts TDM of publicly available data. Should the copyright reform pass as it currently it, it may drive successful European startups out of Europe.
Policy Makers don't see the day-to-day implications of TDM
Ubermetrics founder and CEO Patrick Bunk explains how the current copyright reform could create a lot of uncertainties for European startups conducting TDM activities in Europe.
INFOGRAPHIC: Unlocking the Benefits of Text & Data Mining in Europe
TDM helps and ensures Europe's competitiveness and future prosperity
TDM can help bring the benefits of Research to everyone
The EU has a huge opportunity to increase the uptake of TDM if it gets it rights says Lenard Koschwitz from Allied for Startups @FutureTDM Workshop
An introduction to Text and Data Mining from the Betty & Gordon Moore Library, University of Cambridge
Using machine learning and AI to reduce hospital readmissions
How researchers use TDM to identify ways to reduce hospital readmissions for chronic conditions and provide corresponding actionable guidelines for patient-provider teams
Moodstock: a French startup used TDM to create a "Shazam for images"
Moodstocks is a French image recognition company whose technology is described as the “Shazaam” for images. It compares images taken by a consumer using their phone with an annotated, indexed set of images it stored on its servers.
The technology employed recognises user-uploaded pictures of posters, magazine photos, and product shots.
To train their image recognition technology Moostock used machine learning of third party content.