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 3historical 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.
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.
1 class AutocompleteSystem {
2 private final Map<String, Integer> cache = new HashMap<String, Integer>();
3 private String input = "";
4
5 public AutocompleteSystem(String[] sentences, int[] times) {
6 for (int i = 0; i < sentences.length; i++) {
7 cache.put(sentences[i], times[i]);
8 }
9 }
10
11 public List<String> input(char c) {
12 if (c == ‘#‘) {
13 Integer count = cache.getOrDefault(input, 0);
14 cache.put(input, ++count);
15 input = "";
16 return Collections.emptyList();
17 }
18
19 input += c;
20 return cache.entrySet().stream()
21 .filter(e -> e.getKey().startsWith(input))
22 .sorted(Map.Entry.<String, Integer>comparingByValue(Comparator.reverseOrder())
23 .thenComparing(Map.Entry.comparingByKey()))
24 .limit(3)
25 .map(Map.Entry::getKey)
26 .collect(Collectors.toCollection(ArrayList::new));
27 }
28 }
1 class AutocompleteSystem {
2 class TrieNode {
3 Map<Character, TrieNode> children;
4 Map<String, Integer> counts;
5 boolean isWord;
6
7 public TrieNode() {
8 children = new HashMap<>();
9 counts = new HashMap<>();
10 isWord = false;
11 }
12 }
13
14 TrieNode root;
15 String prefix;
16
17 public AutocompleteSystem(String[] sentences, int[] times) {
18 root = new TrieNode();
19 prefix = "";
20 for (int i = 0; i < sentences.length; i++) {
21 add(sentences[i], times[i]);
22 }
23 }
24
25 private void add(String s, int count) {
26 TrieNode cur = root;
27 for (char c : s.toCharArray()) {
28 TrieNode next = cur.children.get(c);
29 if (next == null) {
30 next = new TrieNode();
31 cur.children.put(c, next);
32 }
33 cur = next;
34 cur.counts.put(s, cur.counts.getOrDefault(s, 0) + count);
35 }
36 cur.isWord = true;
37 }
38
39 public List<String> input(char c) {
40 if (c == ‘#‘) {
41 add(prefix, 1);
42 prefix = "";
43 return new ArrayList<String>();
44 }
45
46 prefix = prefix + c;
47 TrieNode cur = root;
48 for (char ch : prefix.toCharArray()) {
49 TrieNode next = cur.children.get(ch);
50 if (next == null) {
51 return new ArrayList<String>();
52 }
53 cur = next;
54 }
55
56 PriorityQueue<Map.Entry<String, Integer>> pq = new PriorityQueue<>((a,
57 b) -> (a.getValue() == b.getValue() ? a.getKey().compareTo(b.getKey()) : b.getValue() - a.getValue()));
58 for (Map.Entry<String, Integer> entry : cur.counts.entrySet()) {
59 pq.add(entry);
60 }
61
62 List<String> res = new ArrayList<>();
63 for (int i = 0; i < 3 && !pq.isEmpty(); i++) {
64 res.add(pq.poll().getKey());
65 }
66 return res;
67 }
68 }
原文地址：https://www.cnblogs.com/beiyeqingteng/p/11186741.html