Detecting Human Emovere through Data Mining
P. Rani1 , M.V. Jagannatha Reddy2 , K.S.M.V. Kumar3 , Sreedhar S.B.4
Section:Research Paper, Product Type: Journal Paper
Volume-8 ,
Issue-1 , Page no. 64-69, Jan-2020
CrossRef-DOI: https://doi.org/10.26438/ijcse/v8i1.6469
Online published on Jan 31, 2020
Copyright © P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B., “Detecting Human Emovere through Data Mining,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.1, pp.64-69, 2020.
MLA Style Citation: P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B. "Detecting Human Emovere through Data Mining." International Journal of Computer Sciences and Engineering 8.1 (2020): 64-69.
APA Style Citation: P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B., (2020). Detecting Human Emovere through Data Mining. International Journal of Computer Sciences and Engineering, 8(1), 64-69.
BibTex Style Citation:
@article{Rani_2020,
author = {P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B.},
title = {Detecting Human Emovere through Data Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2020},
volume = {8},
Issue = {1},
month = {1},
year = {2020},
issn = {2347-2693},
pages = {64-69},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4997},
doi = {https://doi.org/10.26438/ijcse/v8i1.6469}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i1.6469}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4997
TI - Detecting Human Emovere through Data Mining
T2 - International Journal of Computer Sciences and Engineering
AU - P. Rani, M.V. Jagannatha Reddy, K.S.M.V. Kumar, Sreedhar S.B.
PY - 2020
DA - 2020/01/31
PB - IJCSE, Indore, INDIA
SP - 64-69
IS - 1
VL - 8
SN - 2347-2693
ER -
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Abstract
With the growth of the Internet community, textual data has proven to be the main tool of communication in human-human interaction. This communication is constantly evolving towards the goal of making it as human and real as possible. One way of humanizing such interaction is to provide a framework that can recognize the emotions present in the communication or the emotions of the involved users in order to enrich user experience. The use of social networking sites is one of the approaches for putting views of user. Proposed emotion detector system takes a text document or audio and the emotion word ontology as inputs and produces the scores of six emotion classes (i.e. happy, sad, fear, surprise, anger and disgust) as the output; for twitter data as input the extracted tweets are categorized in to positive, negative and neutral tweets.
Key-Words / Index Term
Human-Computer Interaction; Textual Emotion Recognition; speech analysis; twitter analysis; Emotion Word Ontology
References
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