Paper Info
Title
Mining Arabic Business Reviews
Abstract
For languages with rich content over the web, business reviews are easily accessible via many known websites, e.g., Yelp.com. For languages with poor content over the web like Arabic, there are very few websites (we are actually aware of only one that is indeed unpopular) that provide business reviews. However, this does not mean that such reviews do not exist. They indeed exist unstructured in websites not originally intended for reviews, e.g., Forums and Blogs. Hence, there is a need to mine for those Arabic reviews from the web in order to provide them in the search results when a user searches for a business or a category of businesses. In this paper, we show how to extract the business reviews scattered on the web written in the Arabic language. The mined reviews are analyzed to also provide their sentiments (positive, negative or neutral). This way, we provide our users the information they need about the local businesses in the language they understand, and therefore provide a better search experience for the Middle East region, which mostly speaks Arabic.
Year
DOI
Venue
2010
10.1109/ICDMW.2010.24
Data Mining Workshops
Keywords
Field
DocType
mining arabic business reviews,arabic review,business review,known web,user search,rich content,poor content,arabic language,local business,better search experience,search result,business,search engines,middle east,feature extraction,internet,data mining
Data science,Data mining,World Wide Web,Arabic,Computer science,Business data processing,Feature extraction,Middle East,The Internet
Conference
ISBN
Citations 
PageRank 
978-0-7695-4257-7
21
1.02
References 
Authors
2
2
Name
Order
Citations
PageRank
Mohamed Elhawary1794.40
Mohamed Elfeky2211.02