Adaptive Faceted Search for Product Comparison on the Web of Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

In this paper, we study the appropriateness of adaptive faceted search as a search paradigm for e-commerce on the Web of Data. We provide preliminary evidence that the product space in a sample dataset narrows down logarithmically by the number of product features used in a query, and show that the usability of an adaptive, instance-driven faceted search interface is comparable to approaches with hard-wired product features, while improving the depth of product search and comparison.

Keywords

E-commerce Product comparison Faceted search Usability SUS HCI Linked data Semantic Web RDF SPARQL 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Universitaet der Bundeswehr MunichNeubibergGermany

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