Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/455
DC FieldValueLanguage
dc.contributor.authorXie, Haoran-
dc.contributor.authorWang, Philips Fu Lee-
dc.contributor.authorPoon, Chung Keung-
dc.contributor.authorWong, Tak Lam-
dc.contributor.otherZou, D.-
dc.date.accessioned2021-03-29T10:30:32Z-
dc.date.available2021-03-29T10:30:32Z-
dc.date.issued2017-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/455-
dc.description.abstractWe have developed a method called skill2vec, which applies big data techniques to automatically analyze the learning data to discover skill relationship, leading to a more objective and data-informed decision making. Skill2vec is a neural network architecture which can transform a skill to a new vector space called embedding. The embedding can facilitate the comparison and visualization of different skills and their relationship. We conducted a pilot experiment using benchmark dataset to demonstrate the effectiveness of our method.en_US
dc.language.isoenen_US
dc.publisherAssociation for Computing Machineryen_US
dc.titleAn automatic approach for discovering skill relationship from learning dataen_US
dc.typeconference proceedingsen_US
dc.relation.publicationLAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conferenceen_US
dc.contributor.affiliationSchool of Computing and Information Sciences-
dc.relation.isbn9781450348706en_US
dc.description.startpage608en_US
dc.description.endpage609en_US
dc.cihe.affiliatedYes-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypeconference proceedings-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptRita Tong Liu School of Business and Hospitality Management-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptSchool of Computing and Information Sciences-
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