LeetCode Design Search Autocomplete System
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:
- The hot degree for a sentence is defined as the number of times a user typed the exactly same sentence before.
- 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).
- If less than 3 hot sentences exist, then just return as many as you can.
- When the input is a special character, it means the sentence ends, and in this case, you need to return an empty list.
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:
- The input sentence will always start with a letter and end with ‘#’, and only one blank space will exist between two words.
- 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.
- Please use double-quote instead of single-quote when you write test cases even for a character input.
- Please remember to RESET your class variables declared in class AutocompleteSystem, as static/class variables are persisted across multiple test cases. Please see herefor more details.
本题要求实现一个搜索引擎的自动补全功能，正好是我想在我的新闻搜索引擎里实现的功能。首先会给出一些历史数据，就是哪些句子被访问了多少次。现在模拟用户输入，每输入一个字符，给出以输入的所有字符为前缀的历史句子，并且只给出被访频率前3的句子作为自动补全的候选。 Trie树的应用题。Trie树的节点属性包含is_sentence_以该字符结尾是否是一个句子，cnt_该句子的频率。首先把历史数据插入到Trie树中，记录好相应的is_sentence_和cnt_。 用一个成员变量cur_sentence_记录当前输入的字符串前缀。查找的时候，用cur_sentence_在Trie树中找，先找到这个前缀，然后在26个字母+一个空格中递归查找所有孩子节点，把能形成句子的字符串及其频率插入到一个优先队列中。该优先队列先以句子频率排序，如果频率相等，再以字典序排列。这样我们直接从优先队列中取出前三个堆顶句子，就是自动补全的候选。 如果遇到#，说明输入结束，把cur_sentence_及其频率1也插入到Trie树中。注意插入之后树中节点的频率是累加的，即第34行。 注意AutocompleteSystem类初始化的时候需要清空cur_sentence_和Trie树，更多的细节请看代码中的caution。 [cpp] const int N = 26; class AutocompleteSystem { private: struct Node { bool is_sentence_; int cnt_; vector<Node*> children_; Node() :is_sentence_(false), cnt_(0){ for (int i = 0; i < N + 1; ++i)children_.push_back(NULL); } }; Node *root; string cur_sentence_; struct Candidate { int cnt_; string sentence_; Candidate(int &cnt, string &sentence) :cnt_(cnt), sentence_(sentence) {}; bool operator<(const Candidate& cand) const { return (cnt_ < cand.cnt_) || (cnt_ == cand.cnt_&&sentence_ > cand.sentence_); // caution } }; void AddSentence(const string& sentence, const int& time) { Node *cur = root; for (const auto& c : sentence) { int idx = c – ‘a’; if (c == ‘ ‘)idx = N; if (cur->children_[idx] == NULL)cur->children_[idx] = new Node(); cur = cur->children_[idx]; } cur->is_sentence_ = true; cur->cnt_ += time; // caution } void FindSentences(Node *root, string &sentence, priority_queue<Candidate>& candidates) { if (root != NULL&&root->is_sentence_)candidates.push(Candidate(root->cnt_, sentence)); if (root == NULL)return; for (int i = 0; i < N + 1; ++i) { if (root->children_[i] != NULL) { if (i == N) sentence.push_back(‘ ‘); else sentence.push_back(‘a’ + i); FindSentences(root->children_[i], sentence, candidates); sentence.pop_back(); } } } void StartWith(priority_queue<Candidate>& candidates) { Node *cur = root; for (const auto& c : cur_sentence_) { int idx = c – ‘a’; if (c == ‘ ‘)idx = N; if (cur->children_[idx] == NULL)return; cur = cur->children_[idx]; } string sentence = cur_sentence_; FindSentences(cur, sentence, candidates); } public: AutocompleteSystem(vector<string> sentences, vector<int> times) { root = new Node(); // caution cur_sentence_ = ""; // caution for (int i = 0; i < sentences.size(); ++i)AddSentence(sentences[i], times[i]); } vector<string> input(char c) { if (c == ‘#’) { AddSentence(cur_sentence_, 1); // caution cur_sentence_ = ""; // caution return{}; } else { cur_sentence_.push_back(c); priority_queue<Candidate> candidates; StartWith(candidates); if (candidates.empty())return{}; vector<string> ans; while (!candidates.empty()) { ans.push_back(candidates.top().sentence_); candidates.pop(); if (ans.size() == 3)break; } return ans; } } }; [/cpp] 本代码提交AC，用时329MS。]]>