KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
Online Publication Date2017-12-30
Print Publication Date2017
Permanent link to this recordhttp://hdl.handle.net/10754/626737
MetadataShow full item record
AbstractAcademic search engines (e.g., Google scholar or Microsoft academic) provide a medium for retrieving various information on scholarly documents. However, most of these popular scholarly search engines overlook the area of data set retrieval, which should provide information on relevant data sets used for academic research. Due to the increasing volume of publications, it has become a challenging task to locate suitable data sets on a particular research area for benchmarking or evaluations. We propose Delve, a web-based system for data set retrieval and document analysis. This system is different from other scholarly search engines as it provides a medium for both data set retrieval and real time visual exploration and analysis of data sets and documents.
CitationAkujuobi U, Zhang X (2017) Delve: A Data Set Retrieval and Document Analysis System. Lecture Notes in Computer Science: 400–403. Available: http://dx.doi.org/10.1007/978-3-319-71273-4_39.
Conference/Event nameMachine Learning and Knowledge Discovery in Databases