Deep learning based techniques have been recently used with promising results for data
integration problems. Some methods directly use pre-trained embeddings that were trained …

Data curation–the process of discovering, integrating, and cleaning data–is one of the
oldest, hardest, yet inevitable data management problems. Despite decades of efforts from …

Entity alignment aims to match synonymous entities across different knowledge graphs,
which is a fundamental task for knowledge integration. Recently, researchers have devoted …

Data integration is utilized to integrate heterogeneous data from multiple sources,
representing a crucial step to improve information value in data analysis and mining …

Deep learning techniques have been used with promising results for data integration
problems. Some methods use pre-trained embeddings that were trained on a large corpus …

Deep learning based techniques have been recently used with promising results for data
integration problems. Some methods directly use pre-trained embeddings that were trained …

Lexical Similarity (LS) between two languages uncovers many interesting linguistic insights
such as phylogenetic relationship, mutual intelligibility, common etymology, and loan words …

Data retention is a pervasive and far-reaching topic, affecting everything from academia to
industry. Current solutions rely on manual work by domain users, but they are not adequate …

Data cleaning is one of the most important but time-consuming tasks for data scientists. The
data cleaning task consists of two major steps:(1) error detection and (2) error correction …

Respective text feature sets and non-text feature sets are generated corresponding to
individual pairs of a plurality of record pairs. At least one text feature is based on whether a …