Semantic annotation based exploratory search for information analysts |
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| Authors: | Jae-wook Ahn Peter Brusilovsky Jonathan Grady Daqing He Radu Florian |
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| Institution: | 1. Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK;2. Inria, Villers-lès-Nancy 54600, France;3. Mitsubishi Electric Research Laboratories, Cambridge, MA 02139-1955, USA;1. Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK;2. Inria, Villers-lès-Nancy F-54600, France;3. Mitsubishi Electric Research Laboratories, Cambridge, MA 02139, USA;1. School of Computer and Control Engineering, University of China Academy Science, Beijing, China;2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China |
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| Abstract: | The system presented in this article aims to improve information access through the use of semantic annotation utilizing a non-traditional approach. Instead of applying semantic annotations to enhance the internal information access mechanisms, we use them to empower the user of an information access system through an innovative named entity-based user interface – NameSieve. NameSieve was built to support an intelligence analyst during the process of exploratory search, an advanced type of search requiring multiple iterations of retrieval interleaved with browsing and analyzing the retrieved information. The proposed approach was implemented in the NameSieve system so that the system can transparently present a summary of search results in the form of entity “clouds.” Therefore, these clouds allow the analyst to further explore the results in a novel manner, acting together as a faceted browsing interface. We ran a user study (with ten subjects) to examine the effect of NameSieve, and the study results reported in the paper demonstrate that this new way of applying semantic annotation information was actively used and was evaluated positively by the subjects. It enabled the subjects to work more productively and bring back most relevant documents. |
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