Abstract

Conference on Cloud Computing, Big Data & Emerging Topics JCC-BD&ET 2021: Cloud Computing, Big Data & Emerging Topics pp 73–88Cite as Proposal for a Classifier for Public Tenders for Software Based on Standard IEEE830 Jorge Hochstetter, Claudio Díaz, Mauricio Diéguez & Jaime Díaz Conference paper First Online: 16 August 2021 322 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1444) Abstract Nowadays, governments and private sectors request industry software solutions through public tenders that use websites for mass distribution. Not only is demand organized, but a large number of software tenders is produced. This study focuses on the analysis of texts from these documents to characterize them efficiently in order to find a specific solution to the general problem of how to make a bid and how not to make a bid. An automatic classifier is proposed for the public tender process for software based on IEEE standard 830-1998, which categorizes text from a pragmatic point of view. Development phases and classification success rates are shown for each algorithm used in the different experiments. This system may be an alternative for the early analysis of public tenders for software with fuzzy requirements.