argrecsys Goto Github PK
Name: ArgRecSys Team @ UAM
Type: Organization
Bio: Research team focused on argument-based recommender systems. We are part of the Information Retrieval Group (IRG) at UAM.
Location: Madrid, Spain
Name: ArgRecSys Team @ UAM
Type: Organization
Bio: Research team focused on argument-based recommender systems. We are part of the Information Retrieval Group (IRG) at UAM.
Location: Madrid, Spain
Description of the ArgRecSys organization.
A compilation of the most famous/used argument mining corpora in English.
Implementation of a traditional classifier of argumentative components (claims and premises), trained with features/metadata previously extracted from manually annotated argumentative sentences from the citizen proposals available in the Decide Madrid platform.
ArgIR: Tool for annotation and retrieval of argumentative information from textual content. A case study in the Decide Madrid database. The search runs on Apache Lucene and the results (proposals and comments) are re-ranked according to the number of arguments they have.
Deep Learning architectures for solving argument mining tasks.
This repository contains a simple but efficient implementation of an argument-based recommender system, which makes use of NLP techniques and a taxonomy and lexicon of connectors to extract argument graphs from the proposals and citizen debates available in the Decide Madrid e-participation platform.
ARGAEL is an open-source Java desktop application designed to maximize the experience and efficiency of the process of annotating and evaluating arguments in large text corpora.
Repository with a two-level taxonomy of argument relations and a relatively large set of linguistic connectors (in English and Spanish) classified with the taxonomy.
Repository with the labels and annotations made on the Decide Madrid 2019 dataset, using different types of annotation tools.
Chatbot of the Decide Madrid 2019 system (with and without arguments).
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