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Mining e-commerce data from e-shop websites

 
: Horch, Andrea; Kett, Holger; Weisbecker, Anette

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE TrustCom/BigDataSE/ISPA 2015. Vol.2: BigDataSE 2015, 9th International Conference on Big Data Science and Engineering. Proceedings : 20-22 August 2015, Helsinki, Finland
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2015
ISBN: 978-1-4673-7951-9
ISBN: 978-1-4673-7952-6
S.153-160
International Conference on Big Data Science and Engineering (BigDataSE) <9, 2015, Helsinki>
International Workshop on Data, Text, Web, and Social Network Mining (DTWSM) <2, 2015, Helsinki>
European Commission EC
FP7-SME; 315637; SME E-COMPASS
E-COMmerce Proficient Analytics in Security and Sales for SMEs
Englisch
Konferenzbeitrag
Fraunhofer IAO ()

Abstract
E-commerce is a constantly growing and competitive market. Comparing product prices is an important task for online retailers as well as for e-shoppers. Online merchants compare their prices to those of their competitors for being able to adjust their prices on the market in order to remain competitive whereas the consumers want to find the best price for a specific product. Since internet prices are updated once a day or even more often and there is a huge number of product offers on the Web the product and price data need to be identified, collected and compared by an automated approach. This paper contributes a novel approach for the automated identification and extraction of product price data from arbitrary e-shop websites which is independent from the e-shops’ language and the product domain. The adequacy of the proposed approach is demonstrated and evaluated through an experiment.

: http://publica.fraunhofer.de/dokumente/N-375162.html