Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/40333
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dc.contributor.authorMinku, Leandro-
dc.contributor.authorHou, Siqing-
dc.date.accessioned2017-09-06T13:27:41Z-
dc.date.issued2017-11-08-
dc.identifier.citationProceedings of The 13th International Conference on Predictive Models and Data Analytics in Software Engineering, November 8th 2017, Toronto, Canada.en
dc.identifier.isbnTBC-
dc.identifier.urihttp://dl.acm.org/icps.cfmen
dc.identifier.uriTBCen
dc.identifier.urihttp://hdl.handle.net/2381/40333-
dc.descriptionThe file associated with this record is under embargo until publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.en
dc.description.abstractxen
dc.language.isoenen
dc.publisherACMen
dc.rightsCopyright © 2017, ACM. Deposited with reference to the publisher’s open access archiving policy.en
dc.titleClustering Dycom: An Online Cross-Company Software Effort Estimation Studyen
dc.typeConference Paperen
dc.description.statusPeer-revieweden
dc.description.versionPost-printen
dc.description.presentedPromise'17, The 13th International Conference on Predictive Models and Data Analytics in Software Engineering, November 8th 2017, Toronto, Canada.en
dc.date.end2017-11-08-
dc.date.start2017-11-08-
pubs.organisational-group/Organisationen
pubs.organisational-group/Organisation/COLLEGE OF SCIENCE AND ENGINEERINGen
pubs.organisational-group/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Computer Scienceen
dc.rights.embargodate2017-11-08-
dc.dateaccepted2017-07-20-
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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