JedAI^3 : beyond batch, blocking-based Entity Resolution

Abstract

JedAI is anopen-sourcetoolkit that allows for building and benchmarking thousands of schema-agnostic Entity Resolution (ER) pipelines through a non-learning, blocking-based end-to-end workflow. In this paper, we present its latest release, JedAI3, which conveys two new end-to-end workflows: one for budgetJedAI-core Data Reading Input SC SJ SC JedAI-gui Set methods Data Store agnostic ER that is based on similarity joins, and one for budgetaware (i.e., progressive) ER. This version also adds support for pre-trained word or character embeddings and connects JedAI to the Python data analysis ecosystem. Overall, these enhancements provide JedAI with features offered by no other ER tool, Data Store Output BB BC CC EM EC EC Blocking-based ER Workflow BB CC Pr Join-based ER Workflow EM EC Evaluation Data Writing especially in the schema- and domain-agnostic context