@article{(Open Science Index):https://publications.waset.org/pdf/10183,
	  title     = {Automatic Extraction of Features and Opinion-Oriented Sentences from Customer Reviews},
	  author    = {Khairullah Khan and  Baharum B. Baharudin and  Aurangzeb Khan and  Fazal_e_Malik},
	  country	= {},
	  institution	= {},
	  abstract     = {Opinion extraction about products from customer
reviews is becoming an interesting area of research. Customer
reviews about products are nowadays available from blogs and
review sites. Also tools are being developed for extraction of opinion
from these reviews to help the user as well merchants to track the
most suitable choice of product. Therefore efficient method and
techniques are needed to extract opinions from review and blogs. As
reviews of products mostly contains discussion about the features,
functions and services, therefore, efficient techniques are required to
extract user comments about the desired features, functions and
services. In this paper we have proposed a novel idea to find features
of product from user review in an efficient way. Our focus in this
paper is to get the features and opinion-oriented words about
products from text through auxiliary verbs (AV) is, was, are, were,
has, have, had. From the results of our experiments we found that
82% of features and 85% of opinion-oriented sentences include AVs.
Thus these AVs are good indicators of features and opinion
orientation in customer reviews.},
	    journal   = {International Journal of Economics and Management Engineering},
	  volume    = {4},
	  number    = {2},
	  year      = {2010},
	  pages     = {102 - 106},
	  ee        = {https://publications.waset.org/pdf/10183},
	  url   	= {https://publications.waset.org/vol/38},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 38, 2010},
	}