Knowledge Acquisition

The process of evoking, exploring, regulating and systematising knowledge on a specific domain to organise it semantically in a knowledge-based system.

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Text Mining Neuroscience Literature using the OpenMinTeD Platform
Intended audience Industry and Business, 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 the Neuroscience use case available at the OpenMinTeD platform can facilitate the curation of neuroscience entities from the literature with the aim of supporting ongoing curation efforts in the Blue Brain Project (BBP), at the École Polytechnique Fédérale de Lausanne (EPFL).
 

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Using the OpenMinTeD platform to aid curators of the ChEBI database
Intended audience Industry and Business, 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 the use case of “Extract Metabolites and their Properties and Modes of Actions”. The tutorial describes step-by-step how to create a workflow in the OpenMinTeD platform that can read input from a source and annotate entities useful for the curation of the ChEBI database.
 

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How to add semantic knowledge resources to the OMTD platform?
Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

The purpose of this tutorial is to explain how to add annotation resources to the OMTD platform. In this context, annotation resources mean ontologies or vocabularies selected in different ontology repositories like AgroPortal.
 

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Tutorial on Text Mining over Viticulture Bibliographic Data
Intended audience Industry and Business, 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 the use case application on Agriculture, and more specifically Viticulture, can be utilized by researchers of this domain on a specific topic by using the components and the workflows that are available at the OpenMinTed Platform.

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Tutorial on Text mining over Food Safety and Water Health Bibliographic Data
Intended audience Industry and Business, 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 the use case application around the Food Safety thematic area, and more specifically around Food Safety and Water Health, can be utilized by researchers of this domain on a specific topic by using the components and the workflows that are available at the OpenMinTed Platform.

Manual annotation with AlvisAE web service : How annotate relations?
By  Estelle Chaix
Publication year: 2016  |  Knowledge Acquisition
Information extraction and other NLP task
By  Martin Krallinger
Publication year: n.d.  |  Text And Data Mining  |  Knowledge Acquisition  |  Knowledge Discovery  |  Knowledge Representation  |  Relation Extraction
Text-mining methods used for information extraction in plant scientific papers Part 6
By  Estelle Chaix
Publication year: 2017  |  Open Access Definition  |  Text And Data Mining  |  Knowledge Acquisition  |  Information Extraction
What can semantic text-mining do for food quality improvement? (Open Science Fair 2017 presentation)
By  Claire Nédellec , Robert Bossy (speaker), Estelle Chaix, Louise Deléger
Publication year: 2017  |  Knowledge Acquisition  |  Information Extraction
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EU flag This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 612425.
This project has also received funding from the European Union's Horizon2020 programme for research, technological development and demonstration under agreement no 741839.