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@ -135,6 +135,17 @@ def postorder(self, root):
3. two items with an equal priority are dequeued based on their order in the queue
<br>
----
### n-ary tree
<br>
* if a tree is a rooted tree in which each node has no more than N children, it's called N-ary tree.
<br>
----
@ -143,14 +154,35 @@ def postorder(self, root):
<br>
* a variant of n-ary tree in which characters are stored in each node
* each path down the tree represents a word
* the * nodes (null nodes) are often used to indicate complete words (usually represented by a special type of child) or a boolean flag that terminates the parent node
* a node can have anywhere from 1 through alphabet_size + 1 child
* can be used to store the entire english language for quick prefix lookup (O(k), where k is the length of the string)
* tries, also called prefix tree, are a variant of n-ary tree in which characters are stored in each node.
* each trie node represents a string (a prefix) and each path down the tree represents a word. note that not all the strings represented by trie nodes are meaningful.
* the root is associated with the empty string.
* the * nodes (null nodes) are often used to indicate complete words (usually represented by a special type of child) or a boolean flag that terminates the parent node.
* a node can have anywhere from 1 through alphabet_size + 1 child.
* can be used to store the entire english language for quick prefix lookup (O(k), where k is the length of the string). they are also widely used on autocompletes, spell checkers, etc.
* tries structures can be represented by arrays and maps or trees.
<br>
#### insertion
<br>
* similar to a bst, when we insert a value to a trie, we need to decide which path to go depending on the target value we insert.
* the root node needs to be initialized before you insert strings.
<br>
#### search
<br>
* all the descendants of a node have a common prefix of the string associated with that node, so it should be easy to search if there are any words in the trie that starts with the given prefix.
* we go down the tree depending on the given prefix, once we cannot find the child node, the search fails.
* we can also search for a specific word rather than a prefix, treating this word as a prefix and searching in the same way as above.
* if the search succeeds, we need to check if the target word is only a prefix of words in the trie or if it's exactly a word (for example, by adding a boolean flag).
<br>
---