## 4 Results and Discussions
### RQ.2 What Functionalities Are Offered by the Jurisprudence Search Systems? Concerning the functionalities of the textual bases processing system, 47% of the agencies participating in the survey informed that the textual bases processing system has filters by categories, such as date of issuance, type of process, units, areas of interest, subjects, among others. On the other hand, 41% of the agencies were neutral, and 12% of agencies stated that the system developed does not have this functionality, as presented in Figure 10 (Q21). Figure 10 (Q22) shows 69% of the agencies strongly agree and agree that the textbase processing system uses logical operators (and, or, not, among others), 15% of the agencies were neutral, and 15% strongly disagree and disagree. 40% of the agencies strongly agree and agree that the textual base processing system offers the possibility to export the search result to pdf, CSV format, among others, 35% of the agencies were neutral, and 25% strongly disagree and disagree (Figure 10 (Q23)). Regarding whether the textual base processing system indexes content from other agencies, only 38% strongly agree and agree, 50% were neutral, and 12% strongly disagree and disagree (Figure 10 (Q24)). Figure 9: LGPD compliance and usability best practices. Hence, 38% of the agencies stated that the textual base processing system indexes various documents, such as digital, PDF, Word, Excel, etc. However, 33% of the agencies were neutral, and 29% of the agencies strongly disagree and disagree (Figure 10 (Q25). In addition, 24% of the agencies stated that the textbase processing system uses some method to define the relevance of documents, 53% were neutral, and 24% stated that the agency does not use any method (Figure 10 (Q26)). Among the methods used to define document relevance, some agencies stated:  
_\"Lucene's standard_ relevance calculation is used, based on term count, term frequency, inverted document frequency, and field size.\"  
_\"Relevance by publication date.\"_  
_\"The Ranking features offered by SQL Server Full Text Search are used, for sorting the results.\"_  
_\"The ElasticSearch database has a method of gauging document relevance from the queried term.\"_  
Figure 10 (Q28) shows that 27% of the agencies stated that their textual base processing system uses a controlled vocabulary. 53% of the agencies were neutral, and 20% stated that the system used by the agency does not have a controlled vocabulary. Toward, 12% of the agencies' textbase processing systems that participated in the survey reported using some Ontology in their solutions. 25% of the agencies were neutral, and 62% reported that they do not use any Ontology (Figure 10 (Q30)). Figure 10: Jurisprudence Search System Features. This finding reveals that the Jurisprudence Search system developed in the context of this research has as one of the main differentials compared to the systems developed by other agencies in its development, the use of Ontologies. Only one agency participating in the survey stated that the textual base processing system uses multimedia data extraction, such as deduplication of audio and video files. This finding also reveals a differentiation from our system Figure 10 (Q32). Just 18% of the agencies reported that there is some study/publication on the use of Artificial Intelligence in the agency's textual base processing system, 36% were neutral and 45% reported that there is no study for the use of AI, as presented in Figure 10 (Q46). Forty-nine agencies reported that their agency does not use statistical methods in the textual bases processing system. Eight agencies stated that they used supervised classification, document classification, similarity, and document clustering. About text mining techniques the agency uses in the textual bases processing system, 12 agencies reported document classification, and ten agencies use document similarity. Six agencies reported that they use document clustering, and six agencies reported that they use document summary.