High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantifi...
Satya Sanket Sahoo, Christopher Thomas, Amit P. Sh...
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or ...
To compensate for the inherent impedance mismatch between the relational data model (tables of tuples) and XML (ordered, unranked trees), tree join algorithms have become the prev...
Schema matching is a critical problem for integrating heterogeneous information sources. Traditionally, the problem of matching multiple schemas has essentially relied on finding ...