trie

问题 I really enjoy using Chrome's URL bar because it remembers commonly-visited sites and often suggests a good completion based on what I've typed and/or visited before. So, for example, I can type t in the URL bar and Chrome will automatically fill it in with twitter.com , or I can type maps and Chrome will fill in the .google.com . This gives me the convenience of data-driven domain name shortcuts without having to maintain an explicit list. What I'm wondering, though, is how Chrome determines

问题 I was trying to understand the radix tree (or compact prefix tree) data structure. I understand how lookup, insert and delete works with it. But I could not understand what does radix mean in a radix tree. What is the purpose of radix here? 回答1: As already mentioned by @ta in the Wikipedia etymology link, the 'radix', is the the base of your trie. In this case we mean the numeric base, and we'll consider storing binary data. Radix R = 2 ^ x, where x >= 1. Take the example of a binary (2-ary)

问题 I have a trie that I've built from a dictionary of words. I want to use this for spell checking( and suggest closest matches in the dictionary , maybe for a given number of edits x). I'm thinking I'd use levenshtein distance between the target word and words in my dictionary, but is there a smart way to traverse the trie without actually running the edit distance logic over each word separately? How should I do the traversal and the edit distance matching? For e.g, if I have words MAN, MANE,

问题 I have a txt file containing 1 million English word with their frequencies in this format: good 345667 bad 456777 ... I　need to store it using either a HashMap or a Trie data structure in Java. Later on I need to look up words from the list without other operations. My understanding is that, the look up is slower for HashMap than Trie, but Trie will take up more memory usage, and the implementation of a Trie also takes effort, while HashMap already is ready for use. For production code, do

问题 I am confused as to how the Trie implementation saves space & stores data in most compact form! If you look at the tree below. When you store a character at any node, you also need to store a reference to that & thus for each character of the string you need to store its reference. Ok we saved some space when a common character arrived but we lost more space in storing a reference to that character node. So isn't there a lot of structural overhead to maintain this tree itself ? Instead if a

问题 My understanding how autocomplete/search for text/item works at high level in any scalable product like Amazon eCommerce/Google at high level was :- Elastic Search(ES) based approach Documents are stored in DB . Once persisted given to Elastic search, It creates the index and store the index/document(based on tokenizer) in memory or disk based configuration. Once user types say 3 characters, it search all index under ES(Can be configured to index even ngram) , Rank them based on weightage and

问题 I don't know if this is the place to ask about algorithms. But let's see if I get any answers ... :) If anything is unclear I'm very happy to clarify things. I just implemented a Trie in python. However, one bit seemed to be more complicated than it ought to (as someone who loves simplicity). Perhaps someone has had a similar problem? My aim was to minimize the number of nodes by storing the largest common prefix of a sub-trie in its root. For example, if we had the words stackoverflow ,

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . Is there any library or documentation/link which gives more information of implementing Trie data structure in java? Any help would be great! Thanks. 回答1: You could read up on Java Trie or look at trie. 回答2: There's a java implementation in Robert Sedgewick's book on algorithms. It's very basic, i.e., no

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . Is there any speed- and cache-efficient implementations of trie in C/C++? I know what a trie is, but I don't want reinvent the wheel, implementing it myself. 回答1: if you are looking for an ANSI C implementation you can "steal" it from FreeBSD. The file you are looking for is called radix.c. It's used for

问题 I'm trying to program a trie in C to read a file and add all the words in the file to the trie, and it works well, but I can't get it to accept apostrophes: typedef struct node { bool wordBool; struct node* next[27]; // 26 letters and one space for the apostrophe } node; node* base; int numWords = 0; bool load(const char* dictionary) { FILE* dictionaryf = fopen(dictionary, "r"); // the file to read base = malloc(sizeof(node)); node variable; node *currNode = &variable; int n = 0; while((n =