Clean-Clean ER Datasets with FastText embeddings

This is a collection of 11 real-world datasets for Clean-Clean ER. Every dataset contains the aggregate attribute values per entity (i.e., a concatenation of all individual attribute values) as well as the value for the most frequent and distinctive attribute. In both cases, the corresponding pre-trained fastText embeddings are available, too. The datasets are the following: D1: Restaurants D2: Abt-Buy D3: Amazon-Google Products D4: DBLP-ACM D5: IMDB-TMDB D6: IMDB-TVDB D7: TMDB-TVDB D8: Amazon-Walmart D9: DBLP-Scholar D10: Movies For more details, please refer to ContinuousFilteringBenchmark and to the corresponding technical report. The 11th datasets comprises two versions of the DBPedia English Infoboxes. Please refer to this publication for more details. We have also added 7 synthetic datasets for Dirty ER of increasing size, which are ideal for scalability analyses. These datasets, which contain demographic information, are the following (their names indicate their size): D10K D50K D100K D200K D300K D1M D2M At the moment, the repository contains the original datasets in JSO format. The datasets in CSV format along with their fastText embeddings are currently available here.