Ontology population from web product information

Abstract

With the vast amount of information available on the Web, there is an increasing need to structure Web data in order to make it accessible to both users and machines. E-commerce is one of the areas in which growing data congestion on the Web has serious consequences. This paper proposes a framework that is capable of populating a product ontology using tabular product information from Web shops. By formalizing product information in this way, better product comparison or recommendation applications could be built. Our approach employs both lexical and syntactic matching for mapping properties and instantiating values. The performed evaluation shows that instantiating consumer electronics from Best Buy and Newegg.com results in an F1 score of approximately 77%.

Developing a Product Knowledge Graph of Consumer Electronics to Manage Sustainable Product Information

“…In the field of e-commerce, knowledge graphs are applied in product search and recommendation. Research has been conducted on representing product information with ontology models such as GoodRelations [18], Consumer Electronics Ontology [7], and Schema.org [19,20]. Furthermore, various studies have been conducted to establish large-scale knowledge graphs at a commercial level.…”

“…en-US.txt (accessed on 10 October 2020)) and categorizing consumer electronics or enabling product search functions. Several studies have proposed ontology models for home appliances [7]. Meanwhile, as electronic devices become diversified and product functions more complex, knowledge models can enable the representation of comprehensive vocabularies and their relationships, using a hierarchical structure ordering relations among various vocabularies.…”