Auto-Suggest (Auto-Complete) “thing” has been around for a few years. Here’s my little snippet on
the subject. For one of my projects, I had to deal
with a non-trivial set of items to be pulled via auto-suggest used by multiple concurrent users. Simple, dumb iteration through a list
in local cache or back-end access didn’t quite cut it. Enter a nifty little structure, perfectly suited for storing and matching verbal data: “Trie” (http://tinyurl.com/db56g) also known as a Pre-fix Tree: “Unlike a binary search tree, no node
in the tree stores
the key associated
with that node; instead, its position
in the tree defines
the key
with which it is associated. All
the descendants of a node have a common prefix of
the string associated
with that node, and
the root is associated
with the empty string. Values are normally not associated
with every node, only
with leaves and some inner nodes that correspond to keys of interest.” This is a very scalable, performing structure. Though, as usual, something ‘fast’ comes at a cost of ‘size’; fortunately RAM is more plentiful today so I can live
with that. I won’t bore you
with the detailed algorithmic performance here - Google can do a better job of such. So, here’s C# implementation of all this. Let’s start
with individual node: Trie Node /// <summary> /// Contains datum of a single trie node. /// </summary> public class AutoSuggestTrieNode { public char Value { get; set; } /// <summary> /// Gets a value indicating whether this instance is leaf node. /// </summary> /// <value> /// <c>true</c> if this instance is leaf node; otherwise, a prefix node <c>false</c>. /// </value> public bool IsLeafNode { get; private set; } public List<AutoSuggestTrieNode> DescendantNodes { get; private set; } /// <summary> /// Initializes a new instance of
the <see cref="AutoSuggestTrieNode"/> class. /// </summary> /// <param name="value">The phonetic value.</param> /// <param name="isLeafNode">if set to <c>true</c> [is leaf node].</param> public AutoSuggestTrieNode(char value = ' ', bool isLeafNode = false) { Value = value; IsLeafNode = isLeafNode; DescendantNodes = new List<AutoSuggestTrieNode>(); } /// <summary> /// Gets
the descendants of
the pre-fix node, if any. /// </summary> /// <param name="descendantValue">The descendant value.</param> /// <returns></returns> public AutoSuggestTrieNode GetDescendant(char descendantValue) { return DescendantNodes.FirstOrDefault(descendant => descendant.Value == descendantValue); } } Quite self-explanatory, imho. A node is either a “Pre-fix” or a “Leaf” node. “Leaf” contains
the full “word”, while
the “Pre-fix” nodes act as indices used for matching
the results. Ok, now
the Trie: Trie Structure /// <summary> /// Contains structure and functionality of an AutoSuggest Trie (Pre-fix Tree) /// </summary> public class AutoSuggestTrie { private readonly AutoSuggestTrieNode _root = new AutoSuggestTrieNode(); /// <summary> /// Adds
the word to
the trie by breaking it up to pre-fix nodes + leaf node. /// </summary> /// <param name="word">Phonetic value.</param> public void AddWord(string word) { var currentNode = _root; word = word.Trim().ToLower(); for (int i = 0; i < word.Length; i++) { var child = currentNode.GetDescendant(word[i]); if (child == null) /* this character hasn't yet been indexed
in the trie */ { var newNode = new AutoSuggestTrieNode(word[i], word.Count() - 1 == i); currentNode.DescendantNodes.Add(newNode); currentNode = newNode; } else currentNode = child; /* this character is already indexed, move down
the trie */ } } /// <summary> /// Gets
the suggested matches. /// </summary> /// <param name="word">The phonetic search value.</param> /// <returns></returns> public List<string> GetSuggestedMatches(string word) { var currentNode = _root; word = word.Trim().ToLower(); var indexedNodesValues = new StringBuilder(); var resultBag = new ConcurrentBag<string>(); for (int i = 0; i < word.Trim().Length; i++) /* traverse
the trie collecting closest indexed parent (parent can't be leaf, obviously) */ { var child = currentNode.GetDescendant(word[i]); if (child == null || word.Count() - 1 == i) break; /* done looking,
the rest of
the characters aren't indexed
in the trie */ indexedNodesValues.Append(word[i]); currentNode = child; } Action<AutoSuggestTrieNode, string> collectAllMatches = null; collectAllMatches = (node, aggregatedValue) => /* traverse
the trie collecting matching leafNodes (i.e. "full words") */ { if (node.IsLeafNode) /* full word */ resultBag.Add(aggregatedValue); /* thread-safe write */ Parallel.ForEach(node.DescendantNodes, descendandNode => /* asynchronous recursive traversal */ { collectAllMatches(descendandNode, String.Format("{0}{1}", aggregatedValue, descendandNode.Value)); }); }; collectAllMatches(currentNode, indexedNodesValues.ToString()); return resultBag.OrderBy(o => o).ToList(); } /// <summary> /// Gets
the total words (leafs)
in the trie. Recursive traversal. /// </summary> public int TotalWords { get { int runningCount = 0; Action<AutoSuggestTrieNode> traverseAllDecendants = null; traverseAllDecendants = n => { runningCount += n.DescendantNodes.Count(o => o.IsLeafNode); n.DescendantNodes.ForEach(traverseAllDecendants); }; traverseAllDecendants(this._root); return runningCount; } } } Matching operations and Inserts involve traversing
the nodes before
the right “spot” is found. Inserts need be synchronous since ordering of data matters here. However, matching can be done
in parallel traversal using recursion (line 64). Here’s sample usage: [TestMethod] public void AutoSuggestTest() { var autoSuggestCache = new AutoSuggestTrie(); var testInput = @"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer nec odio. Praesent libero. Sed cursus ante dapibus
diam. Sed nisi. Nulla quis sem at nibh elementum imperdiet. Duis sagittis ipsum. Praesent mauris. Fusce nec tellus sed augue semper porta. Mauris massa. Vestibulum lacinia arcu eget nulla. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Curabitur sodales ligula
in libero. Sed dignissim lacinia nunc. Curabitur tortor. Pellentesque nibh. Aenean quam.
In scelerisque sem at dolor. Maecenas mattis. Sed convallis tristique sem. Proin ut ligula vel nunc egestas porttitor. Morbi lectus risus, iaculis vel, suscipit quis, luctus non, massa. Fusce ac turpis quis ligula lacinia aliquet. Mauris ipsum. Nulla metus metus, ullamcorper vel, tincidunt sed, euismod
in, nibh. Quisque volutpat condimentum velit. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Nam nec ante. Sed lacinia, urna non tincidunt mattis, tortor neque adipiscing
diam, a cursus ipsum ante quis turpis. Nulla facilisi. Ut fringilla. Suspendisse potenti. Nunc feugiat mi a tellus consequat imperdiet. Vestibulum sapien. Proin quam. Etiam ultrices. Suspendisse
in justo eu magna luctus suscipit. Sed lectus. Integer euismod lacus luctus magna. Quisque cursus, metus vitae pharetra auctor, sem massa mattis sem, at interdum magna augue eget
diam. Vestibulum ante ipsum primis
in faucibus orci luctus et ultrices posuere cubilia Curae; Morbi lacinia molestie dui. Praesent blandit dolor. Sed non quam.
In vel mi sit amet augue congue elementum. Morbi
in ipsum sit amet pede facilisis laoreet. Donec lacus nunc, viverra nec."; testInput.Split(' ').ToList().ForEach(word => autoSuggestCache.AddWord(word)); var testMatches = autoSuggestCache.GetSuggestedMatches("le"); } ..and
the result: That’s it!
