An Information Retrieval Pipeline for Legislative Documents from the Brazilian Chamber of Deputies

Abstract

This work investigates information retrieval methods to address the existing difficulties on the Preliminary Search, part of the law making process from the Brazilian Chamber of Deputies. For such, different preprocessing approaches, stemmers, language models, and BM25 variants were compared. Two legislative corpora from Chamber were used to build and validate the pipeline. All texts were converted to lowercase and had stopwords, accentuation, and punctuation removed. Words were represented by their stem combined with word unigram and bigram language models. Retrieving the bill that was originated from a specific job request, the BM25L with Savoy stemmer reached a R@20 of 0.7356. After removing queries with inconsistencies or which made reference exclusively to attachments, to other job requests, or to bills, the R@20 increased to 0.94.