DocumentCode :
2191711
Title :
RnR: Extracting Rationale from Online Reviews and Ratings
Author :
Rahayu, Dwi AP ; Krishnaswamy, Shonali ; Alahakoon, Oshadi ; Labbe, Cyril
Author_Institution :
Centre for Distrib. Syst. & Software Eng., Monash Univ., Melbourne, VIC, Australia
fYear :
2010
fDate :
13-13 Dec. 2010
Firstpage :
358
Lastpage :
368
Abstract :
Review mining is a part of web mining which focuses on getting main information from user review. State of the art review mining systems focus on identifying semantic orientation of reviews and providing sentences or feature scores. There has been little focus on understanding the rationale for the ratings that are provided. This paper presents our proposed RnR system for extracting rationale from online reviews and ratings. We have implemented the system for evaluation on online reviews for hotels from TripAdvisor.com and present extensive experimental evaluation that demonstrates the improved computational performance of our approach and the accuracy in terms of identifying the rationale. This RnR system is available for testing from http://rnrsystem.com/RnRSystem.
Keywords :
Web sites; data mining; information retrieval systems; relevance feedback; reviews; RnR system; online ratings rationale extraction; online reviews rationale extraction; user review mining systems; web mining; Review mining; ontology; ratings; rationale;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-9244-2
Electronic_ISBN :
978-0-7695-4257-7
Type :
conf
DOI :
10.1109/ICDMW.2010.167
Filename :
5693321
Link To Document :
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