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642. Design Search Autocomplete System

时间:2018-07-20 11:26:38      阅读:215      评论:0      收藏:0      [点我收藏+]

标签:描述   priority   ascii   bee   operation   lse   design   not   list   

问题描述:

Design a search autocomplete system for a search engine. Users may input a sentence (at least one word and end with a special character ‘#‘). For each character they type except ‘#‘, you need to return the top 3 historical hot sentences that have prefix the same as the part of sentence already typed. Here are the specific rules:

  1. The hot degree for a sentence is defined as the number of times a user typed the exactly same sentence before.
  2. The returned top 3 hot sentences should be sorted by hot degree (The first is the hottest one). If several sentences have the same degree of hot, you need to use ASCII-code order (smaller one appears first).
  3. If less than 3 hot sentences exist, then just return as many as you can.
  4. When the input is a special character, it means the sentence ends, and in this case, you need to return an empty list.

Your job is to implement the following functions:

The constructor function:

AutocompleteSystem(String[] sentences, int[] times): This is the constructor. The input is historical data. Sentences is a string array consists of previously typed sentences. Times is the corresponding times a sentence has been typed. Your system should record these historical data.

Now, the user wants to input a new sentence. The following function will provide the next character the user types:

List<String> input(char c): The input c is the next character typed by the user. The character will only be lower-case letters (‘a‘ to ‘z‘), blank space (‘ ‘) or a special character (‘#‘). Also, the previously typed sentence should be recorded in your system. The output will be the top 3 historical hot sentences that have prefix the same as the part of sentence already typed.

 

Example:
Operation: AutocompleteSystem(["i love you", "island","ironman", "i love leetcode"], [5,3,2,2]) 
The system have already tracked down the following sentences and their corresponding times: 
"i love you" : 5 times 
"island" : 3 times 
"ironman" : 2 times 
"i love leetcode" : 2 times 
Now, the user begins another search: 

Operation: input(‘i‘) 
Output: ["i love you", "island","i love leetcode"] 
Explanation: 
There are four sentences that have prefix "i". Among them, "ironman" and "i love leetcode" have same hot degree. Since ‘ ‘ has ASCII code 32 and ‘r‘ has ASCII code 114, "i love leetcode" should be in front of "ironman". Also we only need to output top 3 hot sentences, so "ironman" will be ignored. 

Operation: input(‘ ‘) 
Output: ["i love you","i love leetcode"] 
Explanation: 
There are only two sentences that have prefix "i "

Operation: input(‘a‘) 
Output: [] 
Explanation: 
There are no sentences that have prefix "i a"

Operation: input(‘#‘) 
Output: [] 
Explanation: 
The user finished the input, the sentence "i a" should be saved as a historical sentence in system. And the following input will be counted as a new search. 

 

Note:

    1. The input sentence will always start with a letter and end with ‘#‘, and only one blank space will exist between two words.
    2. The number of complete sentences that to be searched won‘t exceed 100. The length of each sentence including those in the historical data won‘t exceed 100.
    3. Please use double-quote instead of single-quote when you write test cases even for a character input.
    4. Please remember to RESET your class variables declared in class AutocompleteSystem, as static/class variables are persisted across multiple test cases. Please see here for more details.

 

 

解题思路:

可以用trie树来解决这个问题。

由于要返回前3个搜索次数最多的句子,我们可以用priority_queue来存储所返回的所有的句子和它的次数的键值对。

首先构造trie tree,主要为trieNode的结构以及insert 方法。

构造完trieNode类后, 这个系统实际上主要为一个巨大的trietree,我们需要一个树的根节点。

由于我们每次都要输入一个字符,我们可以用一个私有的Node:curNode来追踪当前我们节点。

curNode初始化为root,在每次输入完一个句子时,即输入的字符为‘#’时,我们需要将其置为root

同时需要一个string类型stn来表示当前的搜索的句子。

 

需要注意的是我们priority_queue中存储的为pair<string,int>我们需要给它重写比较器。

所以我们每输入一个字符,首先检查是不是结尾标识“#”,如果是的话,将当前句子加入trie树,重置相关变量,返回空数组。

如不是,检查当前TrieNode对应的child是否含有c的对应节点。如果没有,将curNode置为NULL并且返回空数组。

 

若存在,将curNode 更新为c对应的节点,并且对curNode进行dfs。

dfs时,我们首先检查当前是不是一个完整的句子,如果是,将句子与其次数同时加入priority_queue中,然后对其child中可能存在的子节点进行dfs。

 

进行完dfs后,我们需要取出前三个,需要注意的是,可能可选择的结果不满3个,所以要在while中多加入检测q为空的条件语句。

最后要将q中的所有元素都弹出。

 

代码:

class TrieNode{
  public:
    string str;
    int cnt;
    unordered_map<char, TrieNode*> child;
    TrieNode(): str(""), cnt(0){};
};

struct cmp{
    bool operator() (const pair<string, int> &p1, const pair<string, int> &p2){
        return p1.second < p2.second || (p1.second == p2.second && p1.first > p2.first);
    }
};

class AutocompleteSystem {
public:
    AutocompleteSystem(vector<string> sentences, vector<int> times) {
        root = new TrieNode();
        for(int i = 0; i < sentences.size(); i++){
            insert(sentences[i], times[i]);
        }
        curNode = root;
        stn = "";
    }
    
    vector<string> input(char c) {
        if(c == #){
            insert(stn, 1);
            stn.clear();
            curNode = root;
            return {};
        }
        stn.push_back(c);
        if(curNode && curNode->child.count(c)){
            curNode = curNode->child[c];
        }else{
            curNode = NULL;
            return {};
        }
        
        dfs(curNode);
        
        vector<string> ret;
        int n = 3;
        while(n > 0 && !q.empty()){
            ret.push_back(q.top().first);
            q.pop();
            n--;
        }
        while(!q.empty()) q.pop();
        
        return ret;
    }
    
    void dfs(TrieNode* n){
        if(n->str != ""){
            q.push({n->str, n->cnt});
        }
        for(auto p : n->child){
            dfs(p.second);
        }
    }
    
    void insert(string s, int cnt){
        TrieNode* cur = root;
        for(auto c : s){
            if(cur->child.count(c) == 0){
                cur->child[c] = new TrieNode();
            }
            cur = cur->child[c];
        }
        cur->str = s;
        cur->cnt += cnt;
    }
    
private:
    TrieNode *root, *curNode;
    string stn;
    priority_queue<pair<string,int>, vector<pair<string, int>>, cmp > q;
    
};

/**
 * Your AutocompleteSystem object will be instantiated and called as such:
 * AutocompleteSystem obj = new AutocompleteSystem(sentences, times);
 * vector<string> param_1 = obj.input(c);
 */

 

642. Design Search Autocomplete System

标签:描述   priority   ascii   bee   operation   lse   design   not   list   

原文地址:https://www.cnblogs.com/yaoyudadudu/p/9339362.html

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