Entity Resolution (ER), a core task of Data Integration, detects different entity profiles that
correspond to the same real-world object. Due to its inherently quadratic complexity, a series …

In this paper, we study the problem of using deep neural networks (DNNs) for estimating the
cardinality of similarity queries. Intuitively, DNNs can capture the distribution of data points …

Cloud computing is one of the most used distributed systems for data processing and data
storage. Due to the continuous increase in the size of the data processed by cloud …

Efficiency techniques are an integral part of Entity Resolution, since its infancy. In this
survey, we organized the bulk of works in the field into Blocking, Filtering and hybrid …

Distributed computing, such as Cloud, provides traditional workflow applications with
completely new deployment architecture offering high performance and scalability …

Data dependencies are a key concept in data management and have been researched in
data integration, data quality and query optimization. With the increasing use of graph …

Similarity query is the family of queries based on some similarity metrics. Unlike the
traditional database queries which are mostly based on value equality, similarity queries aim …

Similarity join has become very important for semi-or un-structured data processing and
analysis. Although several studies have been conducted on the similarity join, little attention …

Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution
(ER) aims to identify entities in KBs which refer to the same real-world object. Recent studies …

A set containment join operates on two set-valued attributes with a subset (⊆⊆) relationship
as the join condition. It has many real-world applications, such as in publish/subscribe …