ABSTRACT
Responding to Request for Proposal (RFP) with comprehensive solutions is central to IT Services business. Typically, an RFP comprises a set of questions spanning across various domain areas. Current industry practices largely rely on Subject Matter Experts to analyze questions and search multiple information sources to come up with the best possible response for a question keeping in view the customer context. With expertise typically in short supply, it becomes increasingly difficult to manage growing RFP volumes. To address this problem we propose a generic solution meta-model and a system that can generate a draft response to an RFP to be augmented manually later. The generation step uses NLP, modelling and search techniques augmented with a knowledge base to generate knowledge search queries to retrieve suitable answers to a set of RFP questions and compose RFP response. In this paper, we share a RFP response generation approach, its implementation, results and lessons learnt from deployment with one of the business units having high volumes of proposal turnover. Initial results show that RFP system is effective in enabling response generation with ~76% mean query precision and 86% mean query recall.
- Ellen M. Voorhees. 2001. The TREC question answering track. Natural Language Engineering, 7(4):361--378. Google ScholarDigital Library
- A. Bouziane, D. Bouchiha, N. Doumi, and M. Malki. Question Answering Systems: Survey and Trends. Procedia Computer Science, 73:366--375, 2015. AWICT 2015.Google Scholar
- M. Fernandez, I. Cantador, V. Lopez, D. Vallet, P. Castells, and E. Motta. Semantically enhanced Information Retrieval: An ontology-based approach. J. Web Sem., 9(4):434--452, 2011. Google ScholarDigital Library
- Uren, V., Cimiano, P., Iria, J., Handschuh, S., Vargas-Vera, M., Motta, E. & Ciravegna, F.: Semantic Annotation for Knowledge Management: requirements and a Survey of the State of the Art. Journal of Web Semantics 4(1), 14--28, 2006 Google ScholarDigital Library
- Hochstetter, J., & Cares, C. (2012, November). Call for Software Tenders: Features and Research Problems. In Proceedings of the 7th International Conference on Software Engineering Advances (ICSEA (Vol. 12).Google Scholar
- Paech B., Heinrich R., Zorn-Pauli G., Jung A., Tadjiky S. (2012) Answering a Request for Proposal -- Challenges and Proposed Solutions. In: Regnell B., Damian D. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2012. Lecture Notes in Computer Science, vol 7195. Springer, Berlin, Heidelberg Google ScholarDigital Library
- Renault, S., Mendez, s., Franch, X., Quer, C.: A pattern-based method for building requirements documents in call-for-tender processes. International Journal of Computer Science (2011) 1--28Google Scholar
- Searcy, T.: RFPs Suck! Channel V Books (2009)Google Scholar
- Hamid R. Motahari-Nezhad, Juan M. Cappi, Taiga Nakamurra, Mu Qiao, RFPCog: Linguistic-based Identification and Mapping of Service Requirements in Request for Proposals (RFPs) to IT Service Solutions, 49th Hawaii International Conference on System Sciences, IEEE, 2016 Google ScholarDigital Library
- Capterra, "Website. http://www.capterra.com/proposal-management-software/ (04 2018)."Google Scholar
- Rfpio, "Website. https://www.rfpio.com/product/ (04 2018)."Google Scholar
- Loopio, "Website. https://www.loopio.com/ (04 2018)."Google Scholar
- J.Hochstetter, C. Cachero, C. Cares, and S. Sepúlveda, "Call for Tender Challenges in Practice: a Field Study," in Proc. XV Congreso Iberoamericano en Software Engineering, Buenos Aires, Argentina, 2012.Google Scholar
- A. Bouziane, D. Bouchiha, N. Doumi, and M. Malki. Question Answering Systems: Survey and Trends. Procedia Computer Science, 73:366--375, 2015. AWICT 2015.Google Scholar
- Allam A. and Haggag M., "The Question Answering Systems: A Survey". International Journal of Research and Reviews in Information Sciences (IJRRIS), Vol. 2, No. 3, September (2012)Google Scholar
- D. C. Nazário, M. A. R. Dantas and J. L. Todesco (2014) "Knowledge Engineering: Survey of Methodologies, Techniques and Tools". IEEE Latin America Transactions, vol. 12, no. 8 de december 2014Google Scholar
- Ittycheriah A., Ratnaparkhi A., Mam-mone R.J., IBestioM's statistical Question Answering System, Actes de TREC9, Gaithersburg, MD, 2000, p. 229--234.Google Scholar
- Min Wu, Xiaoyu Zheng, Michelle Duan, Ting Liu and Tomek Strzalkowski. Question Answering by Pattern Matching, Web-Proofing, Semantic Form Proofing. TREC-12.Notebook.Google Scholar
- Kaufmann, E., A. Bernstein and R. Zumstein, 2006. Querix: A natural language interface to query ontologies based on clarification dialogs. Proceedings of the 5th International Semantic Web Conference, (ISWC' 2006), Citeulike, pp: 980--981.Google Scholar
- W. Song, M. Feng, N. Gu, and L. Wenyin. 2007. Question similarity calculation for FAQ answering, In Proceeding of SKG 07, pages 298--301. Google ScholarDigital Library
- Mihalcea, R. and D. Moldovan. (2001). Document indexing using named entities. Studies in Information and Control, 10(1).Google Scholar
- X. Liu and H. Fang. Latent entity space: a novel retrieval approach for entity-bearing queries. Information Retrieval Journal, 18(6):473--503, December 2015. Google ScholarDigital Library
- C. Xiong and J. Callan. EsdRank: Connecting query and documents through external semi-structured data. In Proc. Of CIKM, pages 951--960, 2015. Google ScholarDigital Library
- W. C. Brandão, R. L. T. Santos, N. Ziviani, E. S. de Moura,and A. S. da Silva. Learning to expand queries using entities. JASIST, 65(9):1870--1883, 2014. Google ScholarDigital Library
- J. Dalton, L. Dietz, and J. Allan. Entity query feature expansion using knowledge base links. In Proc. of SIGIR, pages 365--374, 2014. Google ScholarDigital Library
- X. Liu, F. Chen, H. Fang, and M. Wang. Exploiting entity relationship for query expansion in enterprise search.Information Retrieval Journal, 17(3):265--294, 2014.Google ScholarDigital Library
- Vinay Kulkarni, Sreedhar Reddy, Asha Rajbhoj: Scaling Up Model Driven Engineering - Experience and Lessons Learnt. MoDELS (2) 2010: 331--345 Google ScholarDigital Library
- "The Stanford CoreNLP Toolkit," In Proc. of 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, Maryland, USA, pp 55--60, 2014.Google Scholar
- Fellbaum C., WordNet: An Electronic Lexical Database, MIT Press, Cambridge, MA, 1998.Google ScholarCross Ref
- Sheflott, "Method and apparatus for generating a proposal response," U.S. Patent 5,802,493, September 1, 1998Google Scholar
Index Terms
- A RFP System for Generating Response to a Request for Proposal
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