Petition extraction and department detection from citizens’ petitions for e-government’s benefit
Sura Sabah Rasheed, Ahmed T. Sadiq · AIP conference proceedings · 2022
Today governments improve the process of involvement of their citizens with the aid of information and communication technology. Despite the fact that almost all of government regulations are now available online. However, analyzing these unstructured data is hard due to their size and complexity. On the other hand, the great developments in text mining allowed using it to deal with complex problems rather than just a simple keyword search operation. In this paper, a proposed system for the retrieval of textual information and relationships using text mining approaches is examined. This, therefore, would help policy makers to discover if an association is existing between citizens’ opinions and policies using textual data gathered from blogs and other electronic public forums. Furthermore, an approach for e-governance decision support is proposed, which simulates the Iraqi scenario. Petitions extraction and department detection from citizen’s petitions have achieved using the proposed system. Experimental results using more than 5000 petitions from Baghdad governorate, show that 97% ratio in department detection and 94% ratio in petition extraction.