Information Extraction

The process of automatically extracting relevant information from documents.

Resources

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

This tutorial explains how to use the “Arabidopsis Gene Regulation Extractor” application available from the OpenMinTeD platform. It also explains the scientific issues it addresses, and how results of the TDM process can be exploited by researchers through the FlagDB++ application. It is related to the AS-D “Information Extraction of Mechanisms Involved in Plant” Development use case developed in the OpenMinTeD project.
 

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

This tutorial explains how to use the “Habitat-Phenotype Relation Extractor for Microbes” application available from the OpenMinTeD platform. It also explains the scientific issues it addresses, and how the results of the TDM process can be queried and exploited by researchers through the Florilège application. It is related to the AS-C “Microbial biodiversity” use case developed in the OpenMinTeD project.
 

Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Intermediate: able to

BO-LSTM is a model based on biomedical ontologies and Long short-term memory networks. The model was developed in python, using keras. To demonstrate its utility, we trained a classification model on the DDI corpus, using the ChEBI ontology as the reference ontology. This tutorial shows how to install BOLSTM, classify any text using thi...

Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Advanced: apply

The objective of this component is to scan a tokenized text to detect entries in BabelNet in the input document. This component is the base of entity linking and word sense disambiguation as it detects the candidates to be disambiguated. The component produces WSD item annotations as defined in the DKPro WSD typesystem. Afterwards, disambiguation can be performed by other components (like DKPro WSD). The component has been shared as a Docke...

COURSE: VineSum
Intended audience Text and Data miners
Level: Intermediate: able to

A software component for vine/grape variety named entity extraction and clustering

VineSum is an openMinTeD executable component that, given a collection of documents, it: 

    - Performs NER extraction, identifying four entity types: a) vine varieties b) persons c) locations d...

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.

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 researcher...

By  Martin Krallinger, Ramon Alonso-Allende Erhardt, Alfonso Valencia
Publication year: 2005  |  Text And Data Mining  |  Information Extraction