ProdLight A Lightweight Ontology for Product Description Based on Datatype Properties.pdf

ProdLight A Lightweight Ontology for Product Description Based on Datatype Properties.pdf

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ProdLight A Lightweight Ontology for Product Description Based on Datatype Properties

ProdLight: A Lightweight Ontology for Product Description Based on Datatype Properties Martin Hepp Digital Enterprise Research Institute (DERI), University of Innsbruck mhepp@ Abstract: Web pages representing offerings of products and services are a major source of data for Semantic Web-based e-commerce. This data could be useful for numerous applications, e.g. (1) more precise product search engines and shopping bots, (2) aggregation or enrichment of multi-vendor catalogs using public product descriptions, or (3) the automated discovery of additional alternatives based on the combination of multiple items. While there are already some ontologies for products and services available, they are very large in size (20 – 70,000 classes), and thus not always suitable as ontology imports. In this paper, we take a different approach: We represent the semantics of offerings on the Web using a very lightweight ontology of datatype properties in combination with popular classifications like UNSPSC and eCl@ss. We then demonstrate how this representation can be mapped easily to comprehensive ontologies for products and services like eClassOWL1. Our approach provides a straightforward solution for annotating offerings on the Web while avoiding the overhead of importing fully-fledged products and services ontologies in any single annotation. We can show that our proposal has technical advantages and eliminates legal problems when reusing existing standards. 1. Introduction Web pages representing offerings of products and services are a major source of data for Semantic Web-based e-commerce. This data covers technical and commercial aspects and could be useful for numerous future applications. Firstly, it could be used by novel product search engines and shopping bots that identify suitable alternatives for a given need and a given set of preferences. Secondly, the data could be used for assembling, augmenting, or maintaining multi-vendor catalogues for

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