1. ScholarBank@NUS
  2. 1. Staff
  3. Staff Publications
Please use this identifier to cite or link to this item: https://doi.org/10.1109/MIS.2013.45
DC FieldValue
dc.titleKnowledge-based approaches to concept-level sentiment analysis
dc.contributor.authorCambria, E.
dc.contributor.authorSchuller, B.
dc.contributor.authorLiu, B.
dc.contributor.authorWang, H.
dc.contributor.authorHavasi, C.
dc.date.accessioned2014-12-12T07:55:14Z
dc.date.available2014-12-12T07:55:14Z
dc.date.issued2013
dc.identifier.citationCambria, E., Schuller, B., Liu, B., Wang, H., Havasi, C. (2013). Knowledge-based approaches to concept-level sentiment analysis. IEEE Intelligent Systems 28 (2) : 12-14. ScholarBank@NUS Repository. https://doi.org/10.1109/MIS.2013.45
dc.identifier.issn15411672
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/116880
dc.description.abstractThe guest editors introduce novel approaches to opinion mining and sentiment analysis that go beyond a mere word-level analysis of text and provide concept-level methods. Such approaches allow a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. © 2001-2011 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/MIS.2013.45
dc.sourceScopus
dc.subjectconcept-level sentiment analysis
dc.subjectdata mining
dc.subjectintelligent systems
dc.subjectknowledge mining
dc.subjectonline social data
dc.subjectopinion mining
dc.typeReview
dc.contributor.departmentTEMASEK LABORATORIES
dc.description.doi10.1109/MIS.2013.45
dc.description.sourcetitleIEEE Intelligent Systems
dc.description.volume28
dc.description.issue2
dc.description.page12-14
dc.identifier.isiut000321072700005
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.