subtree - ορισμός. Τι είναι το subtree
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Τι (ποιος) είναι subtree - ορισμός

ABSTRACT DATA TYPE
Child node; Leaf node; Ordered tree data structure; Parent node; Root node; Tree (computing); Ancestor node; Child nodes; Subtree; Internal node; Inner node; Root Node; Internal vertices; Tree data structure; Interior node; Tree (computer science); Tree leaf; Leaf object; Leaf nodes; External node; Parent node (in a tree); Tree path; Subtrees; Sibling node; Non-leaf node; Subchild; Sub-child; Applications of tree data structures; Inverted tree
  • This unsorted tree has non-unique values and is non-binary, because the number of children varies from one (e.g. node 9) to three (node 7). The root node, at the top, has no parent.

Maximum agreement subtree problem         
Draft:Maximum Agreement Subtree Problem; Maximum Agreement Subtree Problem
The maximum agreement subtree problem is any of several closely related problems in graph theory and computer science. In all of these problems one is given a collection of trees T_1,\ldots, T_m each containing n leaves.
Frequent subtree mining         
User:Enterprisey/Frequent subtree mining; User:APerson/Frequent subtree mining
In computer science, frequent subtree mining is the problem of finding all patterns in a given database whose support (a metric related to its number of occurrences in other subtrees) is over a given threshold. It is a more general form of the maximum agreement subtree problem.
Tree (data structure)         
In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, except for the root node, which has no parent.

Βικιπαίδεια

Tree (data structure)

In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, except for the root node, which has no parent. These constraints mean there are no cycles or "loops" (no node can be its own ancestor), and also that each child can be treated like the root node of its own subtree, making recursion a useful technique for tree traversal. In contrast to linear data structures, many trees cannot be represented by relationships between neighboring nodes in a single straight line.

Binary trees are a commonly used type, which constrain the number of children for each parent to at most two. When the order of the children is specified, this data structure corresponds to an ordered tree in graph theory. A value or pointer to other data may be associated with every node in the tree, or sometimes only with the leaf nodes, which have no children.

The abstract data type can be represented in a number of ways, including a list of parents with pointers to children, a list of children with pointers to parents, or a list of nodes and a separate list of parent-child relations (a specific type of adjacency list). Representations might also be more complicated, for example using indexes or ancestor lists for performance.

Trees as used in computing are similar to but can be different from mathematical constructs of trees in graph theory, trees in set theory, and trees in descriptive set theory.