Web Search Results Visualization: Evaluation of Two Semantic Search Engines

Semantic search engines improve the accuracy of search results by understanding the meaning and context of terms as they appear in web documents. But do they also improve the presentation of search results? We discuss this research question and attempt to address it by evaluating two semantic search engines: Sig.ma and Kngine. Our analysis is based on the theory and methods of explorative evaluation studies, the inspection evaluation approach in information visualization, user-oriented evaluation studies, and on quantitative data analysis. Our main conclusion is that visualization used in semantic search engines improves the understanding of search results and the overall search experience by exploiting the semantics of web data.