An empirical evaluation on textual results clustering for web search

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Abstract

Clustering web search results into dynamic clusters and cluster hierarchies has been shown to be promising in reducing the information overload typically found in the ranked list search engines. The study compared sixteen participants' search performance and subjective satisfaction level in using textual clustering and ranked list search interfaces towards conducting assigned and self-designated search tasks. The results show participants searched slightly faster, better, and were more satisfied using the ranked list interface. However, it is worth noting that participants performed slightly well in easy type of questions with the clustering interface, and obtained non-repetitive relevant results not found from using the ranked list interface. The study shows the clustering interface provides the values of highlighting prominent concepts and offering richer context for exploring, learning and discovering related concepts; yet it also induces certain degree of information uncertainty, lost, and anxiety. Discussions on the contrast view of clustering search and suggestions for future studies are also provided.

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