Results 11 to 20 of about 7,953 (261)
Adaptive MapReduce Similarity Joins [PDF]
Proceedings of the 5th ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond, 2018 Similarity joins are a fundamental database operation. Given data sets S and R, the goal of a similarity join is to find all points x in S and y in R with distance at most r. Recent research has investigated how locality-sensitive hashing (LSH) can be used for similarity join, and in particular two recent lines of work have made exciting progress on ...
McCauley, Samuel, Silvestri, Francesco
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Probabilistic string similarity joins [PDF]
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, 2010 Edit distance based string similarity join is a fundamental operator in string databases. Increasingly, many applications in data cleaning, data integration, and scientific computing have to deal with fuzzy information in string attributes. Despite the intensive efforts devoted in processing (deterministic) string joins and managing probabilistic data ...
Jeffrey Jestes +3 more
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Efficient exact similarity joins
, 2010 Similarity joins play an important role in many application areas, such as near duplicate Web page detection, data integration and cleaning, record linkage, and pattern recognition. Consequently, there has been much interest in developing efficient algorithms for this fundamental operation.
Xiao, Chuan
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Parallelizing Set Similarity Joins. [PDF]
, 2022 One of today's major challenges in data science is to compare and relate data of similar nature. Using the join operation known from relational databases could help solving this problem. Given a collection of records, the join operation finds all pairs of records, which fulfill a user-chosen predicate.
Fier, Fabian
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Set similarity joins on mapreduce
Proceedings of the VLDB Endowment, 2018 Set similarity joins, which compute pairs of similar sets, constitute an important operator primitive in a variety of applications, including applications that must process large amounts of data. To handle these data volumes, several distributed set similarity join algorithms have been proposed.
Fabian Fier +4 more
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Adaptive Distributed Streaming Similarity Joins [PDF]
, 2023 How can we perform similarity joins of multi-dimensional streams in a distributed fashion, achieving low latency? Can we adaptively repartition those streams in order to retain high performance under concept drifts? Current approaches to similarity joins
Siachamis, George +5 more
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A framework for XML similarity joins. [PDF]
, 2010 A prime motivation for using XML to directly represent pieces of information is the ability of supporting ad-hoc or 'schema-later' settings. In such scenarios, modeling data under loose data constraints is essential. Of course, the flexibility of XML comes at a price: the absence of a rigid, regular, and homogeneous structure makes many aspects of data
Andrade Ribeiro, Leonardo
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Explanation of Allameh Tabataba'i's Point of View Regarding Physical Resurrection and Answering the Doubts about It [PDF]
تاریخ فلسفه اسلامی, 2022 Physical resurrection has always been one of the important and discussed topics among philosophers. Allameh Tabatabai has presented new opinions in this regard and believes that the human body is resurrected in the afterlife, moves towards the soul and ...
Mohammad Etratdoost
doaj
On link-based similarity join [PDF]
Proceedings of the VLDB Endowment, 2011 Graphs can be found in applications like social networks, bibliographic networks, and biological databases. Understanding the relationship, or links , among graph nodes enables applications such as link prediction, recommendation, and spam detection. In this paper, we propose link-based similarity join
Liwen Sun +4 more
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A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs
IEEE Access, 2020 Clustering is an efficient method for improving the communication performance of Vehicular Ad hoc NETworks (VANETs) that adopt Vehicle to Vehicle (V2V) communications.
Xiang Bi +5 more
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