Paper Info
Title
Extracting Product Offers from e-Shop Websites.
Abstract
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.
Year
DOI
Venue
2015
10.1007/978-3-319-30996-5_12
Lecture Notes in Business Information Processing
Keywords
Field
DocType
Web data extraction,Product record extraction,Tag path clustering
HTML element,World Wide Web,Information retrieval,Computer science,Filter (signal processing),Product data,Cluster analysis,Competitor analysis
Conference
Volume
ISSN
Citations 
246
1865-1348
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Andrea Horch121.45
Holger Kett241.76
Anette Weisbecker320234.72