TaxoPublish: Towards a solution to automatically personalize taxonomies in e-catalogs

Abstract

Taxonomies are utilized in e-catalogs to facilitate customers navigating through a marketplace with the help of hierarchically structured concepts. However, when entering the e-catalog, each customer is shown the identical taxonomy regardless their individual requirements. Customers are distracted when navigating to preferred concepts as those are siblings of not required concepts. Provided progress in dynamic taxonomies, catalog segmentation, and personalized directories lacks in a fully automatic support for modifying the taxonomy according to the user’s requirements. The existing works need an explicit user-query, are missing information about the domain, or require the modification through the provider. In this paper, TaxoPublish expert system based on logic programming is presented. The proposed system predicts the customers requirements for automatically modifying the taxonomy in B2B context. With TaxoPublish, retailers can now provide personalization in the form of personalized e-catalogs without any human effort, and without missing any information about the domain. TaxoPublish is using knowledge provided through a Customer Relationship Management system for predicting customers preferences, and knowledge of a Product Information Management system for performing taxonomic operations based on two novel types of taxonomic concepts. Through the usage of logic programming and the cross-platform database model, TaxoPublish can be applied as expert system over distributed and heterogeneous data warehouse architectures across various domains. The comprehensive experiments on two public and one private database show that TaxoPublish expert system is capable of fully-automatic taxonomy modification with an accuracy similar to the expert manual modifications.