|
Título:
|
Identifying requirements in requests for proposal
|
|
Autor/a:
|
Falkner, Andreas; Palomares Bonache, Cristina; Franch Gutiérrez, Javier; Schenner, Gottfried; Aznar Puyalto, Pablo; Schoerghuber, Alexander
|
|
Otros autores:
|
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació; Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
|
Abstract:
|
Abstract. [Context & motivation] Bidding processes are a usual requirement elicitation instrument for large IT or infrastructure projects. An organization or agency issues a Request for Proposal (RFP) and interested companies may submit compliant offers. [Problem] Such RFPs comprise natural language documents of several hundreds of pages with requirements of various kinds mixed with other information. The analysis of that huge amount of information is very time consuming and cumbersome because bidding companies should not disregard any requirement stated in the RFP.
[Principal ideas/results] This research preview paper presents a first version of a classification component, OpenReq Classification Service (ORCS), which extracts requirements from RFP documents while discarding irrelevant text. ORCS is based on the use of Naïve Bayes classifiers.
We have trained ORCS with 6 RFPs and then tested the component with 4 other RFPs, all of them from the railway safety domain. [Contribution] ORCS paves the way to improved productivity by reducing the manual effort needed to identify requirements from natural language RFPs |
|
Abstract:
|
Peer Reviewed |
|
Materia(s):
|
-Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
-Requirements engineering
-Requirements elicitation
-Requirements identification
-Request for proposal
-Bidding process
-Classification.
-Enginyeria de requisits |
|
Derechos:
|
|
|
Tipo de documento:
|
Artículo - Versión presentada
Objeto de conferencia |
|
Editor:
|
Springer
|
|
Compartir:
|
|
