Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
Traditional indexing techniques are not well suited for complex data types such as spatial, spatio-temporal, and multimedia data types, where an instance is a composite of multipl...
Uncertainty pervades many domains in our lives. Current real-life applications, e.g., location tracking using GPS devices or cell phones, multimedia feature extraction, and sensor...
George Beskales, Mohamed A. Soliman, Ihab F. Ilyas
Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between query scores and data uncertainty ma...
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chua...