## 6 Conclusions  
This paper presents a solution for CADE's Jurisprudence Search system to perform textual database processing. First, we performed the collection, retrieval, and indexing of the terms to build the database. Afterward, we used Artificial Intelligence techniques, statistical methods, summarization techniques, indexing, named entity recognition, natural language processing, and ontology. These techniques provided the Jurisprudence Search system a differential to other Jurisprudence Search systems used by other Brazilian agencies. The main contributions of this system are more accurate search results, treatment of structured and unstructured data from different sources and formats, aiming to build a knowledge base that supports legal decision-making processes and analysis. We also surveyed to identify which Brazilian public administration agencies have textual database processing systems, which use technological resources and artificial intelligence and morphological construction techniques. Our findings revealed that Apache Solr is the main indexing engine used by the systems, and Apache Lucene and the Java language were the most used in developing these systems. However, no agency participating in the survey stated that it uses ontology to organize and structure its information. In addition, more than 85% of the Jurisprudence Search systems used by the agencies are not LGPD compliant. As future work, we will implement further improvements to the Jurisprudence Search system to build a knowledge base, using templates to facilitate the analysis of Jurisprudence opinions. In addition, the use of the system will monitors the users' perceptions regarding the decision support. Conceptualization, V.A.M., V.C.R. and V.E.d.R. ; methodology, E.D.C. and R.T.d.S.J. ; software, V.A.M., L.A.C.C. and F.L.L.d.M. ; validation, R.M.G. and F.L.L.d.M. ; formal analysis, R.T.d.S.J. ; investigation, V.E.d.R., V.A.M. and F.A.M.D. ; resources, L.A.C.C. ; data curation, R.B. ; writing--original draft preparation, A.L.S.O. and E.D.C. ; writing--review and editing, A.L.S.O. and E.D.C. All authors have read and agreed to the published version of the manuscript. This work is supported in part by CNPq-Brazilian National Research Council (Grant 312180/2019-5 PQ-2 and Grant 465741/2014-2 INCT on Cybersecurity), in part by the Administrative Council for Economic Defense (Grant CADE 08700.000047/2019-14), in part by the Brazilian Ministry of the Economy (Grant DIPLA 005/2016 and Grant ENAP 083/2016), in part by the General Attorney of the Union (Grant AGU 697.935/2019), in part by the National Auditing Department of the Brazilian Health System SUS (Grant DENASUS 23106.118410/ 2020-85), and in part by the General Attorney's Office for the National Treasure (Grant PGFN 23106.148934/2019-67). Not applicable. * [PERSON] et al. (2008) [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Ontologies in the Legal Domain. In _Digital Government: E-Government Research, Case Studies, and Implementation_; Integrated Series in Information Systems; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON]; Springer: Berlin/Heidelberg, Germany, 2008; Volume 17, pp. 233-261. [CrossRef]
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