计算机科学
分类
过程管理
对偶(语法数字)
公司治理
体积热力学
数据科学
运筹学
知识管理
人工智能
业务
工程类
量子力学
物理
文学类
艺术
财务
作者
William Maximiliano Carvalho de Melo,Ana Costa,Paulo Cambra
标识
DOI:10.1145/3560107.3560201
摘要
Planning Instruments (PI) are textual documents in the form of plans or strategies that articulate public policies with objectives and goals by the actions of public authorities. PIs offer a large volume of textual information that can change from time to time. Each PI can contain hundreds of objectives and goals with its own indicators, execution rates, and time limits. The volume of PI's information makes it difficult to monitor the execution of all plans and carry out cross-sectional analyses to perceive parallel activities and possible synergies in addressing public policy problems. The present study seeks to respond to the challenge of systematizing these PIs with a dual purpose: On the one hand, it aims to develop a decision support system that allows policymakers to monitor the execution of the different IPs and identify areas with potential for convergence. At the same time, in an open electronic governance model, the system is intended to be available on a public portal, where citizens and stakeholders can research and follow the various public policy indicators. The project will build an algorithm based on natural language processing (NLP) and machine learning. Through text mining, the algorithm will learn how to extract, categorize and compare information from different PIs, such as operational objectives, goals, and execution rates. The last step will be to feed a search engine that will simplify the navigation among other PIs.
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