We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
A key step in the optimization of declarative queries over XML data is estimating the selectivity of path expressions, i.e., the number of elements reached by a specific navigatio...
Natasha Drukh, Neoklis Polyzotis, Minos N. Garofal...
Due to the structural heterogeneity of XML, queries are often interpreted approximately. This is achieved by relaxing the query and ranking the results based on their relevance to ...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
This paper describes a new XML compression scheme that offers both high compression ratios and short query response time. Its core is a fully reversible transform featuring substit...