Supporting Multi-view User Ontology to Understand Company Value Chains

  • Authors:
  • Landong Zuo;Manuel Salvadores;Sm Hazzaz Imtiaz;John Darlington;Nicholas Gibbins;Nigel R Shadbolt;James Dobree

  • Affiliations:
  • Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Intelligence, Agents, Multimedia (IAM) Group, School of Electronics and Computer Science, University of Southampton, UK;Semantric Ltd., London, UK SW8 2EQ

  • Venue:
  • ISWC '09 Proceedings of the 8th International Semantic Web Conference
  • Year:
  • 2009

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Abstract

The objective of the Market Blended Insight (MBI) project is to develop web based techniques to improve the performance of UK Business to Business (B2B) marketing activities. The analysis of company value chains is a fundamental task within MBI because it is an important model for understanding the market place and the company interactions within it. The project has aggregated rich data profiles of 3.7 million companies that form the active UK business community. The profiles are augmented by Web extractions from heterogeneous sources to provide unparalleled business insight. Advances by the Semantic Web in knowledge representation and logic reasoning allow flexible integration of data from heterogeneous sources, transformation between different representations and reasoning about their meaning. The MBI project has identified that the market insight and analysis interests of different types of users are difficult to maintain using a single domain ontology. Therefore, the project has developed a technique to undertake a plurality of analyses of value chains by deploying a distributed multi-view ontology to capture different user views over the classification of companies and their various relationships.