Abstract—Semantic Web promises to add metadata to web
content to make it understandable to computers. Search is the
most widely used activity on web. Semantic search engines have
already changed the way we search the data on web. Uren. V,
Yuanguilei Uren et al., proposed requirement space pyramid
arguing that iterative and exploratory search modes are
important to the usability of search engines. It identified the
types of semantic queries the users need to make, the issues
concerning the search development and the problems intrinsic
to semantic search in particular. We have extensively examined
the semantic search engines and have done broad survey to
analyse the semantic search engines. Comparative analysis of
the semantic search engines have been done on the basis of
factors cited in the pyramid. The research provides deep
understanding of five main semantic search engines based on
comparative analysis that may help for future work for
semantic web in general and for semantic search engines in
particular.
Index Terms—Semantic web, semantic search engine,
requirement space pyramid.
The authors are with the Department of Computer Science, COMSATS
Institute of Information Technology, Attock, Pakistan (e-mail:
Hikmatullah@comsats.edu.pk, maliha_red@hotmail.com,
asmaasmi@live.com).
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Cite:Maliha Majid Qureshi, Bibi Asma, and Hikmat Ullah Khan, "Comparative Analysis of Semantic Search Engines Based
on Requirement Space Pyramid," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 562-566, 2013.
