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 …

String similarity search and join are two important operations in data cleaning and
integration, which extend traditional exact search and exact join operations in databases by …

String similarity join is an important operation in data integration and cleansing that finds
similar string pairs from two collections of strings. More than ten algorithms have been …

String similarity join is an essential operation in data integration. The era of big data calls for
scalable algorithms to support large-scale string similarity joins. In this paper, we study …

We study the problem of edit similarity joins, where given a set of strings and a threshold
value K, we want to output all pairs of strings whose edit distances are at most K. Edit …

We study the string similarity search problem with edit-distance constraints, which, given a
set of data strings and a query string, finds the similar strings to the query. Existing …

Graphs are widely used to model complicated data semantics in many applications in
bioinformatics, chemistry, social networks, pattern recognition, etc. A recent trend is to …

In this paper we study similarity join and search on multi-attribute data. Traditional methods
on single-attribute data have pruning power only on single attributes and cannot efficiently …

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 …

Similarity query processing is becoming increasingly important in many applications such as
data cleaning, record linkage, Web search, and document analytics. In this paper we study …