DSpace Repository

Evaluation of data mining for two child-related, social risk issues

Show simple item record

dc.contributor.author Little, James
dc.contributor.author Waheed, Hayder A.
dc.contributor.author Rixon, Andy
dc.date.accessioned 2023-02-16T12:48:49Z
dc.date.available 2023-02-16T12:48:49Z
dc.date.issued 2017
dc.identifier.citation Little, James; Waheed, Hayder A.; Rixon, Andy (2017). "Evaluation of data mining for two child-related, social risk issues", CEUR Workshop Proceedings, Vol. 2086, pp. 219-231. tr_TR
dc.identifier.issn 1613-0073
dc.identifier.uri http://hdl.handle.net/20.500.12416/6251
dc.description.abstract Two child-related social issues are examined using data mining to determine successful ways of predicting risk. The issues of child truancy and child abuse can be considered similar as both are influenced by, the child’s characteristics, family and environment. The results show that from an initial portfolio of algorithms, a one-nearest neighbour approach works well. We believe that reflects the nature of the problem, where expert opinion classifies each new pupil /case in terms of similar ones, while the one-nearest aspect, reflects the small amount of data we had access to. tr_TR
dc.language.iso eng tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Child Abuse tr_TR
dc.subject Data Mining tr_TR
dc.subject Risk tr_TR
dc.subject Social AI tr_TR
dc.subject Truancy tr_TR
dc.title Evaluation of data mining for two child-related, social risk issues tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal CEUR Workshop Proceedings tr_TR
dc.identifier.volume 2086 tr_TR
dc.identifier.startpage 219 tr_TR
dc.identifier.endpage 231 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record