Toward Semantic Assessment of Vulnerability Severity: A Text Mining Approach

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 160
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorLee, Yongjaeko
dc.contributor.authorShin, Seungwonko
dc.date.accessioned2018-12-20T05:29:24Z-
dc.date.available2018-12-20T05:29:24Z-
dc.date.created2018-11-27-
dc.date.created2018-11-27-
dc.date.issued2018-10-22-
dc.identifier.citation1st International Workshop on EntitY REtrieval (EYRE '18)-
dc.identifier.urihttp://hdl.handle.net/10203/247861-
dc.languageEnglish-
dc.publisherACM-
dc.titleToward Semantic Assessment of Vulnerability Severity: A Text Mining Approach-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85075639309-
dc.type.rimsCONF-
dc.citation.publicationname1st International Workshop on EntitY REtrieval (EYRE '18)-
dc.identifier.conferencecountryIT-
dc.identifier.conferencelocationLingotto, Turin-
dc.contributor.localauthorShin, Seungwon-
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0