TY  - JOUR
T1  - Opinion Mining with Aspects and Shortcuts for Prediction Model
AU - Hafez, Ghada AU - Ismail, Rasha AU - Karam, Omar 
JO  - Asian Journal of Information Technology
VL  - 17
IS  - 3
SP  - 212
EP  - 217
PY  - 2018
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2018.212.217
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2018.212.217
KW  - Aspect mining
KW  -opinion mining
KW  -tempo wrods
KW  -text mining
KW  -shortcuts
KW  -database
AB  - Opinion mining or sentiment analysis extract specified information from a large amount of text or reviews given by the internet users. Opinion mining classifies the large text of opinions as positive (good), negative (bad) or neutral. According to the number of positive, negative and neutral reviews, the product or service will be rated. Most researches neglected the shortcuts of words like (CD “Compact Disc”), (GR8 “means Great”). To avoid classify these words wrong, a database is built for some of these shortcuts with its meaning and orientation (positive, negative or neutral). Also, few researches tried to extract tempo words from text as general not from opinions, so that, a framework is proposed to merge tempo and sentiment analysis to enhance the prediction for the opinions.
ER  -