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The HyperLogLog has three main operations: add to add a new element to the set, count to obtain the cardinality of the set and merge to obtain the union of two sets. Some derived operations can be computed using the inclusion–exclusion principle like the cardinality of the intersection or the cardinality of the difference between two HyperLogLogs combining the merge and count operations.
One-to-many: order ←→ line item: 1: 1..* or + An order contains at least one item Many-to-one: person ←→ birthplace: 1..* or + 1: Many people can be born in the same place, but 1 person can only be born in 1 birthplace Many-to-many: course ←→ student: 1..* or + 1..* or + Students follow various courses Many-to-many (optional on both ...
The goal of a cardinal assignment is to assign to every set A a specific, unique set that is only dependent on the cardinality of A. This is in accordance with Cantor 's original vision of cardinals: to take a set and abstract its elements into canonical "units" and collect these units into another set, such that the only thing special about ...
An example is the following 3-by-3 matrix: A permutation matrix is a special case of a bistochastic matrix, in which each element is either 0 or 1 (so there is exactly one "1" in each row and each column).
Examples of known min/max sketch estimators: Chassaing et al. [4] presents max sketch which is the minimum-variance unbiased estimator for the problem. The continuous max sketches estimator [5] is the maximum likelihood estimator. The estimator of choice in practice is the HyperLogLog algorithm. [6]
In computer science, the Hopcroft–Karp algorithm (sometimes more accurately called the Hopcroft–Karp–Karzanov algorithm) [1] is an algorithm that takes a bipartite graph as input and produces a maximum-cardinality matching as output — a set of as many edges as possible with the property that no two edges share an endpoint.
For example, think of A as Authors, and B as Books. An Author can write several Books, and a Book can be written by several Authors. In a relational database management system, such relationships are usually implemented by means of an associative table (also known as join table, junction table or cross-reference table), say, AB with two one-to-many relationships A → AB and B → AB.
Maximum cardinality matching is a fundamental problem in graph theory. [1] We are given a graph G , and the goal is to find a matching containing as many edges as possible; that is, a maximum cardinality subset of the edges such that each vertex is adjacent to at most one edge of the subset.