loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Christian Rudolf von Rohr 1 ; Hans Friedrich Witschel 2 and Andreas Martin 2

Affiliations: 1 FHNW University of Applied Sciences and Arts Northwestern Switzerland, CH-4600 Olten, Switzerland, Agentur Frontal AG, Willisau and Switzerland ; 2 FHNW University of Applied Sciences and Arts Northwestern Switzerland, CH-4600 Olten and Switzerland

Keyword(s): Effort Estimation, Experience Management, Case-based Reasoning, Machine Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Intelligent Information Systems ; KM Strategies and Implementations ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Organizational Memories ; Symbolic Systems ; Tools and Technology for Knowledge Management

Abstract: In many industries, companies deliver customised solutions to their (business) customers within projects. Estimating the human effort involved in such projects is a difficult task and underestimating efforts can lead to non-billable hours, i.e. financial loss on the side of the solution provider. Previous work in this area has focused on automatic estimation of the cost of software projects and has largely ignored the interaction between automated estimation support and human project leads. Our main hypothesis is that an adequate design of such interaction will increase the acceptance of automatically derived estimates and that it will allow for a fruitful combination of data-driven insights and human experience. We therefore build a recommender that is applicable beyond software projects and that suggests job positions to be added to projects and estimated effort of such positions. The recommender is based on the analysis of similar cases (case-based reasoning), “explains” derived s imilarities and allows human intervention to manually adjust the outcomes. Our experiments show that recommendations were considered helpful and that the ability of the system to explain and adjust these recommendations was heavily used and increased the trust in the system. We conjecture that the interaction of project leads with the system will help to further improve the accuracy of recommendations and the support of human learning in the future. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.221.46.132

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Rohr, C.; Witschel, H. and Martin, A. (2018). Training and Re-using Human Experience: A Recommender for More Accurate Cost Estimates in Project Planning. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KMIS; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, pages 52-62. DOI: 10.5220/0006893200520062

@conference{kmis18,
author={Christian Rudolf von Rohr. and Hans Friedrich Witschel. and Andreas Martin.},
title={Training and Re-using Human Experience: A Recommender for More Accurate Cost Estimates in Project Planning},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KMIS},
year={2018},
pages={52-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006893200520062},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KMIS
TI - Training and Re-using Human Experience: A Recommender for More Accurate Cost Estimates in Project Planning
SN - 978-989-758-330-8
IS - 2184-3228
AU - Rohr, C.
AU - Witschel, H.
AU - Martin, A.
PY - 2018
SP - 52
EP - 62
DO - 10.5220/0006893200520062
PB - SciTePress