1. Tries:Data structure by searching string keys
	1. R-way tries, even faster than red-black BST and hashing
	2. Store characters in nodes
	3. Store values in nodes corresponding to last characters in keys
	4. Search until the ending character with a non-null value
	5. Insertion: create link until the last character and set value in that node
	6. Node: a value +references to R nodes
	7. Search hit: all L characters, search miss: typical sublinear, space: R null links at each leaf
	8. Spell check: 26-way trie
	9. deletion: set the value to null
2. Ternary Search
	1. Store characters and values in nodes
	2. Each node has 3 children: smaller, equal, and larger (3-way)
	3. Search: if less left, if greater right
	4. if equal, take the middle link and move to the next key character (+1)
	5. 3 null links in each leaf (less null links than r-way tries if r>3), much space efficient in large R
	6. Space 4N
	7. Hybrid of r^2-way trie and TST: root has r^2 nodes, even quicker
	8. Faster than hashing and more flexible than red-black BST
3. Character-based operations
	1. Prefix-match, wildcard match
	2. Longest-prefix
	3. Patricia trie: each node represents a sequence of characters
	4. Suffix-tree (Patricia trie of suffixes of a string, linear-time construction)