TaxoCatalog: expert system for semantically personalizing paper-based product catalogs in omni-channel context using background knowledge

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Heiko Angermann


Taxonomies are a formal method of semantically structuring information using hierarchically ordered concepts. Those play a crucial role in omni-channel retailing to publish product catalogs across media channels, i.e. digital (portal-based, paper-based) media channels, and print media (paper-based) media channels. Portal-based media channels use taxonomies to structure product-related content by concepts to facilitate customers navigate through the e-commerce site. That are the product categories. Paper-based media channels require taxonomies for automatic layout setting using data-driven publishing software. When recommender systems are additionally used, products are published individually on the e-commerce site. Printed product catalogs, on the other hand, currently only display content regardless of dynamic preferences, unless the layout is set manually. That is, as in an industrial context, personalization is of no interest if the necessary processes cannot be automated. The only recent industrially relevant method of taking preferences into account is to print sub-catalogs. However, these only contain certain product categories, resulting in a loss of information and sales, as preferences change dynamically today. With TaxoCatalog, an expert system is presented in this paper, capable of semantically personalizing product taxonomies to layout printed product catalogs according to the dynamic preferences of customers. The proposed expert system considers three layers to achieve full automation of relevant processes. The first layer uses background knowledge to consider a memory-based analysis of preferences, and a content-based analysis of possible semantic modifications. The second layer infers semantically personalized taxonomies using different modification rules. The third layer transforms the individual taxonomy paths into XML. This allows that the output of TaxoCatalog can be processed by any standard data-driven publishing software for automatic layout setting. A case study and a comprehensive evaluation, which discusses the strengths and limitations of previous research in the field, as well as the expert system in terms of quantitative and qualitative criteria, underline the efficiency of TaxoCatalog. 

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Angermann, H. (2024). TaxoCatalog: expert system for semantically personalizing paper-based product catalogs in omni-channel context using background knowledge. Journal of Print and Media Technology Research, 12(4), 197–217. Retrieved from
Scientific contributions