prefix-tree

问题 I'm trying to implement a data structure that supports autocomplete on a website. I've managed to implement an iterative version of a Trie. It supports the two primary methods of adding and searching in a Trie. However now I need to add a method that returns all the words that begin with the following prefix. Can someone help me with this. class Trie: def __init__(self): self.root = TrieNode() def insert(self, word): curr = self.root for letter in word: node = curr.children.get(letter) if not

问题 I'm trying to implement a data structure that supports autocomplete on a website. I've managed to implement an iterative version of a Trie. It supports the two primary methods of adding and searching in a Trie. However now I need to add a method that returns all the words that begin with the following prefix. Can someone help me with this. class Trie: def __init__(self): self.root = TrieNode() def insert(self, word): curr = self.root for letter in word: node = curr.children.get(letter) if not

问题 I have written down a simple function that determines if str1 is a prefix of str2. It's a very simple function, that looks like this (in JS): function isPrefix(str1, str2) // determine if str1 is a prefix of a candidate string { if(str2.length < str1.length) // candidate string can't be smaller than prefix string return false; var i = 0; while(str1.charAt(i) == str2.charAt(i) && i <= str1.length) i++; if(i < str1.length) // i terminated => str 1 is smaller than str 2 return false; return true

问题 I'm reading a paper where they mention that they were able to find the single nearest neighbor in O(1) using a prefix tree. I will describe the general problem and then the classical solution and finally the proposed solution in the paper: Problem : given a list of bit vectors L (all vectors have the same length) and query bit vector q, we would like to find the nearest neighbor of q. The distance metric is the hamming distance (how many bits are different). The naive approach would be to go

问题 I am working on storing a list of cities(read from a file) with their corresponding latitude and longitude values. At the end of each city, I am trying to append the longitude and latitude values. So for example, Fremont in the trie would look like F->R->E->M->O->N->T->(latitude and longitude) I am able to successfully insert the values into the trie, but when i try to search for a specific city, the longitude and latitude values return as (null) Here is my implementation void readFile(){ /

问题 Suppose I have a list of strings and a prefix tree of those strings, and I would like to locate a string given a key, which one is more faster? binary search or prefix tree search? Why and what's the time complexity? Thanks! 回答1: Both techniques have their advantages, and their drawbacks: Suffix tree Advantages: O(N) building complexity O(M) search of a pattern of length M They allow online construction Drawbacks: Space inefficient Really complex construction algorithms Binary search (with

问题 The problem I'm trying to solve is explained in this question: Finding the single nearest neighbor using a Prefix tree in O(1)? My question is regarding the Proposed solution section in that question page. In that section it's mentioned that we find the nearest neighbor from each prefix tree by traversing the tree starting from the node. Well looking up if a key exists in a prefix tree is straightforward but getting the most similar one I don't understand at all. How to accomplish this? I

问题 How is the prefix string location handling implemented within nginx? http://nginx.org/r/location Specifically, it's widely reported that the http://nginx.org/r/server_name matching is done through a hash table — http://nginx.org/docs/http/server_names.html — but there isn't a similar level of detail on the implementation of the location directive. 回答1: The prefix-based location tree is defined to have 3 child node elements at each node: http://ngx.su/src/http/ngx_http_core_module.h#ngx_http

问题 I want to implement a trie to check for the validity of paths, so I would have a tree built that contains all the possible path constructions by breaking it down by directory. So something like /guest/friendsList/search would go from the root node to it's child guest , then guest's child friendsList , and then friendsList's child search . If search is a leaf node then my string /guest/friendsList/search would be considered valid. Is this something a trie would be useful for. All the

问题 I'm writing an algorithm that will first take a config file of various endpoints and their associated method like the following: /guest guestEndpoint /guest/lists listEndpoint /guest/friends guestFriendsEndpoint /guest/X/friends guetFriendsEndpoint /guest/X/friends/X guestFriendsEndpoint /X/guest guestEndpoint /X/lists listEndpoint /options optionsEndpoint X here represents a wildcard, so any string would match with this. The algorithm would take this as input and build a tree with each node