{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T23:41:32Z","timestamp":1769730092169,"version":"3.49.0"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030937324","type":"print"},{"value":"9783030937331","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-93733-1_7","type":"book-chapter","created":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T06:02:58Z","timestamp":1645164178000},"page":"104-118","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Applying Machine Learning to Risk Assessment in Software Projects"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3847-2989","authenticated-orcid":false,"given":"Andr\u00e9","family":"Sousa","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3825-3954","authenticated-orcid":false,"given":"Jo\u00e3o Pascoal","family":"Faria","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9081-2728","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Mendes-Moreira","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5187-040X","authenticated-orcid":false,"given":"Duarte","family":"Gomes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0319-4296","authenticated-orcid":false,"given":"Pedro Castro","family":"Henriques","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3944-607X","authenticated-orcid":false,"given":"Ricardo","family":"Gra\u00e7a","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,18]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","volume":"46","author":"N Altman","year":"1992","unstructured":"Altman, N.: An introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46, 175\u2013185 (1992)","journal-title":"Am. Stat."},{"key":"7_CR2","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/52.62930","volume":"8","author":"B Boehm","year":"1991","unstructured":"Boehm, B.: Software risk management: principles and practices. IEEE Softw. 8, 32\u201341 (1991)","journal-title":"IEEE Softw."},{"key":"7_CR3","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/978-3-642-55035-5_5","volume-title":"Software Project Management in a Changing World","author":"B Boehm","year":"2014","unstructured":"Boehm, B.: Software project risk and opportunity management. In: Ruhe, G., Wohlin, C. (eds.) Software Project Management in a Changing World, pp. 107\u2013121. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-3-642-55035-5_5"},{"key":"7_CR4","doi-asserted-by":"publisher","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001). https:\/\/doi.org\/10.1023\/A:1010933404324","DOI":"10.1023\/A:1010933404324"},{"key":"7_CR5","first-page":"60","volume":"6","author":"P Chawan","year":"2013","unstructured":"Chawan, P., Patil, J., Naik, R.: Software risk management. Int. J. Comput. Technol. 6, 60\u201366 (2013)","journal-title":"Int. J. Comput. Technol."},{"key":"7_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-3-319-57858-3_11","volume-title":"Risk Assessment and Risk-Driven Quality Assurance","author":"M Felderer","year":"2017","unstructured":"Felderer, M., Auer, F., Bergsmann, J.: Risk management during software development: results of a survey in software houses from Germany, Austria and Switzerland. In: Gro\u00dfmann, J., Felderer, M., Seehusen, F. (eds.) RISK 2016. LNCS, vol. 10224, pp. 143\u2013155. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-57858-3_11"},{"key":"7_CR7","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"J Friedman","year":"2001","unstructured":"Friedman, J.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 29, 1189\u20131232 (2001)","journal-title":"Ann. Stat."},{"key":"7_CR8","unstructured":"Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: AISTATS (2010)"},{"key":"7_CR9","unstructured":"Group, T.S.: Chaos report 2015 (2015). https:\/\/standishgroup.com\/sample_research_files\/CHAOSReport2015-Final.pdf"},{"key":"7_CR10","doi-asserted-by":"publisher","unstructured":"Hsieh, M.Y., Hsu, Y.C., Lin, C.T.: Risk assessment in new software development projects at the front end: a fuzzy logic approach. J. Ambient Intell. Humanized Comput. 9 (2016). https:\/\/doi.org\/10.1007\/s12652-016-0372-5","DOI":"10.1007\/s12652-016-0372-5"},{"key":"7_CR11","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-981-10-6602-3_3","volume-title":"ICT Based Innovations","author":"P Kaur","year":"2018","unstructured":"Kaur, P., Gosain, A.: Comparing the behavior of oversampling and undersampling approach of class imbalance learning by combining class imbalance problem with noise. In: Saini, A.K., Nayak, A.K., Vyas, R.K. (eds.) ICT Based Innovations. AISC, vol. 653, pp. 23\u201330. Springer, Singapore (2018). https:\/\/doi.org\/10.1007\/978-981-10-6602-3_3"},{"key":"7_CR12","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/978-3-540-24659-6_19","volume-title":"Product Focused Software Process Improvement","author":"O Mizuno","year":"2004","unstructured":"Mizuno, O., Hamasaki, T., Takagi, Y., Kikuno, T.: An empirical evaluation of predicting runaway software projects using Bayesian classification. In: Bomarius, F., Iida, H. (eds.) Product Focused Software Process Improvement, pp. 263\u2013273. Springer, Heidelberg (2004)"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Molnar, C.: Interpretable machine learning (2019). https:\/\/christophm.github.io\/interpretable-ml-book\/","DOI":"10.21105\/joss.00786"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Nguyen, H.M., Cooper, E., Kamei, K.: Borderline over-sampling for imbalanced data classification. Int. J. Knowl. Eng. Soft Data Paradigms 3, 4\u201321 (2011)","DOI":"10.1504\/IJKESDP.2011.039875"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Platt, J.C.: Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In: Advances in Large Margin Classifiers, pp. 61\u201374. MIT Press (1999)","DOI":"10.7551\/mitpress\/1113.003.0008"},{"key":"7_CR16","unstructured":"PMI: A Guide to the Project Management Body of Knowledge (PMBOK Guide), 4th Edn. Project Management Institute (2008)"},{"key":"7_CR17","unstructured":"Rennie, J.D.M., Shih, L., Teevan, J., Karger, D.: Tackling the poor assumptions of Naive Bayes text classifiers. In: ICML (2003)"},{"key":"7_CR18","doi-asserted-by":"publisher","unstructured":"Wallace, L., Keil, M., Rai, A.: Understanding software project risk: a cluster analysis. Inf. Manage. 42(1), 115\u2013125 (2004). https:\/\/doi.org\/10.1016\/j.im.2003.12.007, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0378720604000102","DOI":"10.1016\/j.im.2003.12.007"},{"key":"7_CR19","unstructured":"Westfall, L.: Defining software risk management (2001). http:\/\/www.westfallteam.com\/sites\/default\/files\/papers\/risk_management_paper.pdf"},{"key":"7_CR20","unstructured":"Williams, R.C., Pandelios, G.J., Behrens, S.: Software risk evaluation (SRE) method description (version 2.0) (2000)"},{"key":"7_CR21","doi-asserted-by":"publisher","unstructured":"Wu, J., Chen, X.Y., Zhang, H., Xiong, L.D., Lei, H., Deng, S.H.: Hyperparameter optimization for machine learning models based on bayesian optimization. J. Electron. Sci. Technol. 17(1), 26 \u2013 40 (2019). https:\/\/doi.org\/10.11989\/JEST.1674-862X.80904120, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1674862X19300047","DOI":"10.11989\/JEST.1674-862X.80904120"}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-93733-1_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T21:20:41Z","timestamp":1726694441000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-93733-1_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030937324","9783030937331"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-93733-1_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"18 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2021.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"869","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"210","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-9","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}