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2015
With the increasing ability of current applications to produce and consume more complex data, such as images and geographic information, the similarity join has attracted considerable attention. However, this operator does not consider the relationship among the elements in the answer, generating results with many pairs similar among themselves, which ...
Lúcio F. D. Santos +4 more
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With the increasing ability of current applications to produce and consume more complex data, such as images and geographic information, the similarity join has attracted considerable attention. However, this operator does not consider the relationship among the elements in the answer, generating results with many pairs similar among themselves, which ...
Lúcio F. D. Santos +4 more
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Incremental processing for string similarity join
International Journal of Computational Science and Engineering, 2019Yanglan Gan, Guangwei Xu
exaly +2 more sources
Proceedings of the VLDB Endowment, 2014
String similarity join is an important operation in data integration and cleansing that finds similar string pairs from two collections of strings. More than ten algorithms have been proposed to address this problem in the recent two decades. However, existing algorithms have not been thoroughly compared under the same experimental framework.
Yu Jiang +3 more
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String similarity join is an important operation in data integration and cleansing that finds similar string pairs from two collections of strings. More than ten algorithms have been proposed to address this problem in the recent two decades. However, existing algorithms have not been thoroughly compared under the same experimental framework.
Yu Jiang +3 more
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Similarity Join in Metric Spaces
2003Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbors search primitives. However, the quadratic computational complexity of similarity joins prevents from applications on large data collections.
Dohnal V, Gennaro C, Savino P, Zezula P
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Similarity Joins of Sparse Features
Companion of the 2024 International Conference on Management of DataIdentifying all pairs of records from two datasets whose similarity exceeds a given threshold is crucial for data cleaning and clustering. Our work on similarity-joins is motivated by detecting fraud and abuse. We focus on similarity-joins of sparse features, where records represent sparse sets, multisets, or vectors.
Ahmed Metwally 0001, Michael Shum
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Efficient SimRank-Based Similarity Join
ACM Transactions on Database Systems, 2017Graphs have been widely used to model complex data in many real-world applications. Answering vertex join queries over large graphs is meaningful and interesting, which can benefit friend recommendation in social networks and link prediction, and so on.
Zheng, Weigua +3 more
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Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
Location-based services have attracted significant attention due to modern mobile phones equipped with GPS devices. These services generate large amounts of spatio-textual data which contain both spatial location and textual descriptions. Since a spatio-textual object may have different representations, possibly because of deviations of GPS or ...
Sitong Liu +2 more
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Location-based services have attracted significant attention due to modern mobile phones equipped with GPS devices. These services generate large amounts of spatio-textual data which contain both spatial location and textual descriptions. Since a spatio-textual object may have different representations, possibly because of deviations of GPS or ...
Sitong Liu +2 more
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Efficient Metric Indexing for Similarity Search and Similarity Joins
IEEE Transactions on Knowledge and Data Engineering, 2017Spatial queries including similarity search and similarity joins are useful in many areas, such as multimedia retrieval, data integration, and so on. However, they are not supported well by commercial DBMSs. This may be due to the complex data types involved and the needs for flexible similarity criteria seen in real applications.
Lu Chen 0001 +4 more
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Performance Enhanced Multiset Similarity Joins
2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom), 2016The amount of data produced on a daily basis isgrowing at an exponential rate. One method of filtering throughthis data is the use of similarity joins, or methods that areused to identify similar data. Such algorithms are used fora variety of applications ranging from plagiarism detection tomarketing.
Jahnavi Yalamanchili +3 more
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Trie-based similarity search and join
Proceedings of the Joint EDBT/ICDT 2013 Workshops, 2013Driven by the increasing demands from applications such as data cleansing, integration, and bioinformatics, approximate string matching queries have gain much attention recently. In this paper, we present the design and implementation of a trie-based system which supports both string similarity search and join based on our recent work [23].
Jianbin Qin +3 more
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