E-Commerce video annotation using goodrelations-based LODs with faceted search in smart TV environment

  • Authors:

  • Trong Hai Duong;Ahmad Nurzid Rosli;Visal Sean;Kee-Sung Lee;Geun-Sik Jo

  • Affiliations:

  • Dept. of Computer and Information Engineering, Inha University, Korea;School of Computer and Information Engineering, Inha University, Korea;School of Computer and Information Engineering, Inha University, Korea;School of Computer and Information Engineering, Inha University, Korea;Dept. of Computer and Information Engineering, Inha University, Korea

  • Venue:
  • ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

TV-commerce is a new form of shopping that allows consumer to view, select and buy products from Smart TV. To do so, sellers annotate videos and associate it with information from online e-commerce systems in a semantic manner. In this work, we propose an e-commerce information derivation mechanism for video annotation using Linked Open Data (LOD) with faceted search. Annotation information is derived from e-commerce LODs, which linked distributed data across e-commerce web. We incorporated faceted search to allow consumer to easily make a information derivation query defined by GoodRelations ontology. The derived information is displayed as a faceted graph facilitating information choice.