Efficient processing of top-k queries is a crucial requirement in many interactive
environments that involve massive amounts of data. In particular, efficient top-k processing …

Classical approaches to clean data have relied on using integrity constraints, statistics, or
machine learning. These approaches are known to be limited in the cleaning accuracy …

Data analysts often build visualizations as the first step in their analytical workflow. However,
when working with high-dimensional datasets, identifying visualizations that show relevant …

The rapid growth of the Web in the past two decades has made it the largest publicly
accessible data source in the world. Web mining aims to discover useful information or …

Many modern data science applications build on data lakes, schema-agnostic repositories
of data files and data products that offer limited organization and management capabilities …

Ontologies play a crucial role in the development of the Semantic Web as a means for
defining shared terms in web resources. They are formulated in web ontology languages …

Top-k processing in uncertain databases is semantically and computationally different from
traditional top-k processing. The interplay between score and uncertainty makes traditional …

With the increasing amount of text data stored in relational databases, there is a demand for
RDBMS to support keyword queries over text data. As a search result is often assembled …

Recommending packages of items to groups of users has several applications, including
recommending vacation packages to groups of tourists, entertainment packages to groups of …

Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with
the highest scores according to f. Even though the problem is well-studied in conventional …