BipartiteJoin: Optimal Similarity Join for Fuzzy Bipartite Matching
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F24%3A39921109" target="_blank" >RIV/00216275:25530/24:39921109 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-60328-0_17" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-60328-0_17</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-60328-0_17" target="_blank" >10.1007/978-3-031-60328-0_17</a>
Alternative languages
Result language
angličtina
Original language name
BipartiteJoin: Optimal Similarity Join for Fuzzy Bipartite Matching
Original language description
Set similarity join, crucial for data cleaning, integration, and recommendation systems, identifies set pairs exceeding a similarity threshold. Our approach combines a count Q-gram filter with maximum weighted bipartite matching, balancing accuracy and efficiency. The Qgram filter, based on the relationship between Q-gram similarity and edit distance, reduces the number of comparisons, operating in constant time on a pre-built index. This enables real-time processing, as only a minimal number of pairs are verified through Fuzzy Bipartite Matching, significantly enhancing the efficiency of similarity joins.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Good Practices and New Perspectives in Information Systems and Technologies : WorldCIST 2024, Volume 6
ISBN
978-3-031-60327-3
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
171-180
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Lodž
Event date
Mar 26, 2024
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
001267244400017