|Appears in Collections:||Computing Science and Mathematics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Enhanced SenticNet with affective labels for concept-based opinion mining|
|Citation:||Poria S, Gelbukh A, Hussain A, Howard N, Das D & Bandyopadhyay S (2013) Enhanced SenticNet with affective labels for concept-based opinion mining, IEEE Intelligent Systems, 28 (2), pp. 31-38.|
|Abstract:||SenticNet 1.0 is one of the most widely used, publicly available resources for concept-based opinion mining. The presented methodology enriches SenticNet concepts with affective information by assigning an emotion label.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
National Polytechnic Institute
Computing Science - CSM Dept
Massachusetts Institute of Technology
National Institute of Technology, India
|IS-28-02.pdf||1.88 MB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
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