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One of the widely used algorithms for identifying data duplicates is the "Locality-Sensitive Hashing (LSH)" algorithm. LSH efficiently approximates similarity between data points, making it effective for duplicate detection in large datasets.
Jan 8, 2024
PDF | This paper presents efficient algorithms for clone items de-tection in a binary relation. Best implementation of these algorithms has O(|J|.||M||).
We propose two Data Replica Detection algorithms namely progressive sorted neighborhood method (PSNM), which performs best on small and almost clean datasets, ...
An efficient algorithm for detecting duplicate regions is proposed in this paper. The basic idea is to segment the input image into blocks and search for ...
Missing: clone items
The algorithms we presented here will work more effectively on DAGs, with no change, than on trees. For. DMS, we plan to convert identifiers in tree leaves into.
Missing: Efficient items
Feb 24, 2021 · I have a stream of documents, each having an ID which is a 64 bit unsigned long given as a (maximum length is 20) string. Sometimes an ID appears multiple ...
Missing: clone | Show results with:clone
In this paper, we present a clone detection algorithm for UML domain models. Our approach covers a much greater variety of model types than existing approaches ...
In this paper propose new naive detection algorithm using intelligent guesses which records have a high possibility of representing the same real-world entity, ...
Missing: clone items
and thus we do not expect to find an efficient algorithm that solves the model clone detection problem exactly while still scaling well to models of ...
In this paper, we present an efficient algorithm for identifying similar subtrees and apply it to tree representa- tions of source code. Our algorithm is based ...