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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.
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.