Abstract

With the vast amount of information available on the Web, there is an urgent need to structure Web data in order to make it available to both users and machines. E-commerce is one of the areas in which growing data congestion on the Web impedes data accessibility. This paper proposes FLOPPIES, a framework capable of semi-automatic ontology population of tabular product information from Web stores. By formalizing product information in an ontology, better product comparison or parametric search applications can be built, using the semantics of product attributes and their corresponding values. The framework employs both lexical and pattern matching for classifying products, mapping properties, and instantiating values. It is shown that the performance on instantiating TVs and MP3 players from Best Buy and Newegg.com looks promising, achieving an F1-measure of approximately 77%.

, , , , ,
doi.org/10.1016/j.dss.2014.01.001, hdl.handle.net/1765/68701
ERIM Top-Core Articles
Decision Support Systems
Erasmus School of Economics

Nederstigt, L.J, Aanen, S.S, Vandic, D, & Frasincar, F. (2014). FLOPPIES: A Framework for Large-Scale Ontology Population of Product Information from Tabular Data in E-commerce Stores. Decision Support Systems, 59(1), 296–311. doi:10.1016/j.dss.2014.01.001