Blocking and Filtering Techniques for Entity Resolution: A Survey release_vn7dmwzfdjgctlqnw4qsp2uwse

by George Papadakis, Dimitrios Skoutas, Emmanouil Thanos, Themis Palpanas

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2020  

Abstract

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 techniques, facilitating their understanding and use. We also provided an in-dept coverage of each category, further classifying the corresponding works into novel sub-categories. Lately, the efficiency techniques have received more attention, due to the rise of Big Data. This includes large volumes of semi-structured data, which pose challenges not only to the scalability of efficiency techniques, but also to their core assumptions: the requirement of Blocking for schema knowledge and of Filtering for high similarity thresholds. The former led to the introduction of schema-agnostic Blocking in conjunction with Block Processing techniques, while the latter led to more relaxed criteria of similarity. Our survey covers these new fields in detail, putting in context all relevant works.
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Date   2020-01-07
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arXiv  1905.06167v2
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