Exploiting Semantic Annotation of Content with Linked Open Data (LoD) to Improve Searching Performance in Web Repositories of Multi-disciplinary Research Data

Chapter
Part of the Communications in Computer and Information Science book series (CCIS, volume 573)

Abstract

Searching for relevant information in multi-disciplinary repositories of scientific research data is becoming a challenge for research communities such as the Social Sciences. Researchers use the available keywords-based online search, which often fall short of meeting the desired search results given the known issues of content heterogeneity, volume of data and terminological obsolescence. This leads to a number of problems including insufficient content exposure, unsatisfied researchers and above all dwindling confidence in such repositories of invaluable knowledge. In this paper, we explore the appropriateness of alternative searching based on Linked Open Data (LoD)-based semantic annotation and indexing in online repositories such as the ReStore repository (ReStore repository is an online service hosting and maintaining web resources containing data about multidisciplinary research in Social Sciences. Available at http://www.restore.ac.uk.). We explore websites content annotations using LoD to generate contemporary semantic annotations. We investigate if we can improve accuracy and relevance in search results affected by concepts and terms obsolescence in repositories of scientific content.

Keywords

Search Result Average Precision Mean Average Precision Semantic Annotation Link Open Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Arshad Khan
    • 1
  • Thanassis Tiropanis
    • 1
  • David Martin
    • 2
  1. 1.ECS, University of SouthamptonSouthamptonUK
  2. 2.Geography and EnvironmentUniversity of SouthamptonSouthamptonUK

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