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Extracting product offers from e-shop websites

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


Monfort, Valérie (Ed.):
Web Information Systems and Technologies. 11th International Conference, WEBIST 2015 : Lisbon, Portugal, May 20-22, 2015, Revised Selected Papers
Cham: Springer International Publishing, 2016 (Lecture Notes in Business Information Processing 246)
ISBN: 978-3-319-30995-8 (Print)
ISBN: 978-3-319-30996-5 (Online)
International Conference on Web Information Systems and Technologies (WEBIST) <11, 2015, Lisbon>
European Commission EC
E-COMmerce Proficient Analytics in Security and Sales for SMEs
Fraunhofer IAO ()

On-line retailers as well as e-shoppers are very interested in gathering product records from the Web in order to compare products and prices. The consumers compare products and prices to find the best price for a specific product or they want to identify alternatives for a product whereas the on-line retailers need to compare their offers with those of their competitors for being able to remain competitive. As there is a huge number and vast array of product offers in the Web the product data needs to be collected through an automated approach. The contribution of this papers is a novel approach for automatically identify and extract product records from arbitrary e-shop websites. The approach extends an existing technique which is called Tag Path Clustering for clustering similar HTML tag paths. The clustering mechanism is combined with a novel filtering mechanism for identifying the product records to be extracted within the websites.