Approximate string joins with abbreviations

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Approximate String Joins with Abbreviations

String joins have wide applications in data integration and cleaning. The inconsistency of data caused by data errors, term variations and missing values has led to the need for approximate string joins (ASJ). In this paper, we study ASJ with abbreviations, which are a frequent type of term variation. Although prior works have studied ASJ given a userinputted dictionary of synonym rules, they h...

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Approximate String Joins

String data is ubiquitous and is commonly used to correlate (or join) entities across autonomous, heterogeneous databases. The main challenge is to effectively deal with the noisy nature of string data, due to, for example, transcription errors, incomplete information, and multiple conventions for recording string valued attributes. Commercial databases do not support approximate string joins d...

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Approximate join is an important part of many data cleaning and integration methodologies. Various similarity measures have been proposed for accurate and efficient matching of string attributes. The accuracy of the similarity measures highly depends on the characteristics of the data such as amount and type of the errors and length of the strings. Recently, there has been an increasing interes...

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In [GIJ01a, GIJ01b] we described how to use q-grams in an RDBMS to perform approximate string joins. We also showed how to implement the approximate join using plain SQL queries. Specifically, we described three filters, count filter, position filter, and length filter, which can be used to execute efficiently the approximate join. The intuition behind the count filter was that strings that are...

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String data is ubiquitous, and its management has taken on particular importance in the past few years. Approximate queries are very important on string data especially for more complex queries involving joins. This is due, for example, to the prevalence of typographical errors in data, and multiple conventions for recording attributes such as name and address. Commercial databases do not suppo...

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ژورنال

عنوان ژورنال: Proceedings of the VLDB Endowment

سال: 2017

ISSN: 2150-8097

DOI: 10.14778/3151113.3151118