Beschreibung
Providing a single access point to an information system from multiple sources is helpful in many fields. As a case study, this research investigates the potential of applying information fusion techniques in biodiversity area since researchers in this domain desperately need information from different sources to support decision making on tasks like biological identification. Furthermore, there are massive collections in this area and the descriptive materials on the same species (object) are scattered in different places. It is not easy to manually collect information to form a broader and integrated one. This study demonstrates that to a certain extent, this fusion approach is generalizable. The generalizability of this fusion approach is a challenging problem due to the typical domain- and task- oriented nature of the fusion methods. We identified the challenges while applying the approach to different data set.
Autorenporträt
The author got her Ph.D from Graduate School of Library and Information Science (GSLIS) in University of Illinois at Urbana-Champaign (UIUC) in 2011. Her research interests include information fusion, information retrieval, text mining and information extraction.
