trie

I have to implement the T9 Dictionary . Essentially, when I am pressing any of the 9 keys, it should show me the top 5 words that can be started with that combination of keys. If I type '46', it can give 'hotel' or 'good' depending on whether I intended 'g' or 'h' when I pressed 4. The priority is based on which words are relatively popular - you can use, say, the first 5000 words from the top 100 000 words. The code I am doing is: Import import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.util.Date; import java.util.HashMap; import java.util.LinkedList;

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? 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) trie. The radix is 2, so at each node you can compare one bit . The two children will handle all of the

So, I just ported the Trie from OCaml. Unfortunately, it runs slower than the standard Map in terms of tryFind. I don't understand this - the trie seems like it should be faster. Is F#'s code libraries built in some special way as to make them faster than the code that the user typically deploys? Here's the code - [<RequireQualifiedAccess>] module Trie type Node<'k, 'v when 'k : comparison> = { TrieMap : Map<'k, Node<'k, 'v>> TrieKvp : ('k list * 'v) option } member inline x.IsEmpty = x.TrieKvp.IsNone && x.TrieMap.IsEmpty let inline make map kvp = { TrieMap = map TrieKvp = kvp } let inline

I'm not too well-versed about the actual algorithms used in string matching with tries. I'm wondering why there seems to be more focus on suffix tries for string matching rather than prefix tries. Can we not use prefix tries for substring matching also? Put in another way, what are the advantages of suffix tries over prefix tries? .retteb era seirt xiferp ,drawkcab daer uoy fI Seriously. Suffix tries allow you to traverse from the beginning of a string. 来源： https://stackoverflow.com/questions/6692441/prefix-vs-suffix-trie-in-string-matching

Over the holidays, my family loves to play Boggle. Problem is, I'm terrible at Boggle. So I did what any good programmer would do: wrote a program to play for me. At the core of the algorithm is a simple prefix trie , where each node is a dict of references to the next letters. This is the trie:add implementation: add([], Trie) -> dict:store(stop, true, Trie); add([Ch|Rest], Trie) -> % setdefault(Key, Default, Dict) -> % case dict:find(Key, Dict) of % { ok, Val } -> { Dict, Val } % error -> { dict:new(), Default } % end. { NewTrie, SubTrie } = setdefault(Ch, dict:new(), Trie), NewSubTrie = add

I am looking to implement a VBA trie -building algorithm that is able to process a substantial English lexicon (~50,000 words) in a relatively short amount of time (less than 15-20 seconds). Since I am a C++ programmer by practice (and this is my first time doing any substantial VBA work), I built a quick proof-of-concept program that was able to complete the task on my computer in about half a second. When it came time to test the VBA port however, it took almost two minutes to do the same -- an unacceptably long amount of time for my purposes. The VBA code is below: Node Class Module: Public