QDA: A Query-Driven Approach to Entity Resolution

Query-Driven Approach to Entity Resolution

This paper explores “on-the-fly” data cleaning in the context of a user query. A novel Query-Driven Approach (QDA) is developed that performs a minimal number of cleaning steps that are only necessary to answer a given selection query correctly. The comprehensive empirical evaluation of the proposed approach demonstrates its significant advantage in terms of efficiency over traditional techniqu...

A Query-Driven, Incremental Process for Entity Resolution

HiDER: Query-Driven Entity Resolution for Historical Data

Entity Resolution (ER) is the task of finding references that refer to the same entity across different data sources. Cleaning a data warehouse and applying ER on it is a computationally demanding task, particularly for large data sets that change dynamically. Therefore, a query-driven approach which analyses a small subset of the entire data set and integrates the results in real-time is signi...

QuERy: A Framework for Integrating Entity Resolution with Query Processing

This paper explores an analysis-aware data cleaning architecture for a large class of SPJ SQL queries. In particular, we propose QuERy, a novel framework for integrating entity resolution (ER) with query processing. The aim of QuERy is to correctly and efficiently answer complex queries issued on top of dirty data. The comprehensive empirical evaluation of the proposed solution demonstrates its...

An Incremental Approach to Entity Resolution

We present a query-time entity resolution process that works in a highly parallel fashion. We use the application MobEx to showcase our process, which consists of a mobile client and a server, where the server takes the role of a mediator and carries out the resolution. Results are propagated to the client as early as possible. Resolution results that are produced later in the process are send ...