Resources by relevance

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Intended audience Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

The objective of this tutorial is to showcase how Social Science researchers can take full advantage of the OpenMinTeD TDM platform for Detecting and Linking Variables in Scientific Publications.
 

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Intended audience Policy makers and Funders, Programmers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial describes how to use TDM to build a Recommender system for scholarly resources and utilise OpenMinTed platform to build and annotate corpuses for this purpose.

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Intended audience Industry and Business, Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial is made up of two parts:
Part I is the OpenMinTED guide to create a workflow that reads from a data source and annotate articles related to chronic liver diseases.
Part II is the guide to use the tools to build a graph displaying the progression between liver conditions.
 

Liver diseases and p...

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Intended audience Industry and Business, Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial is made up of two parts:
Part I is the OpenMinTED guide to create a workflow that reads from a data source and annotate articles related to chronic liver diseases.
Part II is the guide to use the tools to build a graph displaying the progression between liver conditions.
 

Liver diseases and p...

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Intended audience Text and Data miners, Industry and Business, Programmers, Researchers and Students
Level: Introductory: no previous knowledge is required

This tutorial focuses on using the Docker image to annotate raw text files. It shows how to install the docker system on a machine, how to pull the UPFMT image and how to pass the input/output parameters and instantiate the container. The user simply has to provide an input folder containing any number of files to be annotated (.txt or .xmi) ...

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Intended audience Text and Data miners, Industry and Business, Programmers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial focuses on using the code directly on a host machine. It gives access to the code (Python) + models and shows the user how to run the code from the console. Also, all the steps needed on how to train new models are given, as well as other pointers. The user will be able to download the code, run a tokenizer/tagger/parser on a se...