我最先想到的解法是先用字典来储存单词出现的个数,再对字典排序,最后拿出前K个,如: #!/usr/bin/env python # -*- coding: utf-8 -*- class Solution(object): def topKFrequent(self, nums, k): """ :type nums: List[int] :type k: int :rtype: List[int] """ data, res = {}, [] ...
func topKFrequent(nums []int, k int) []int { // 统计 nums 中每个数字出现的次数, // 时间复杂度为 O(n) ,空间复杂度为 O(n) numToCnt := make(map[int]int) for _, num := range nums { // num 如果不在 num_to_cnt 中,则初始化为 0 , // 然后对 num 的出现次数加 1 numToCn...
Top-k frequent itemsItem frequency trackingSliding windowMany big data applications today require querying highly dynamic and large-scale data streams to find the top-k most frequent items in the most recent window of a specified size at a specific time. This is a challenging problem. We ...
importjava.util.Map;importjava.util.HashMap;importjava.util.List;importjava.util.ArrayList;classSolution{publicList<Integer>topKFrequent(int[] nums,intk){// 统计元素的频率Map<Integer, Integer> freqMap =newHashMap<>();for(intnum : nums) { freqMap.put(num, freqMap.getOrDefault(num,0) +1...
Mining top-k frequent-regular closed patterns Frequent-regular pattern mining has attracted recently many works. Most of the approaches focus on discovering a complete set of patterns under the user-gi... K Amphawan,P Lenca - 《Expert Systems with Applications》 被引量: 11发表: 2015年 An eff...
It is practical for users to give a parameter K and K "interesting" frequent item sets can be returned as desired. Definition of top-K frequent item sets is presented and the relative natures are discussed. An algorithm to mine accurate top-K frequent item sets from data streams is ...
the number of frequent features of them is often more than data itself, and the retrieval of frequent features by above table-based index structure still needs a high cost. Which makes it challenging to retrieve the top-k frequent items from STBD, especially in the scenario of multi textual ...
Traditional frequent sequential pattern mining only considers the time point-based item or event in the patterns. However, in many application, the events
In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min_l, where k is the desired number of frequent closed patterns to be mined, and min _l is the minimal length of each pattern. An efficient algorithm, called TFP, is developed...
之后,我们返回 items 列表中的前 k个元组的key即可。 3 Python 解题代码 其实小根堆也可以结合 Counter 字典(官方解法一:哈希表+排序),所以我们先演示 Counter。 3.1 Counter - 哈希表+排序 解题代码 ## LeetCode 692E - The K Frequent Word - Counter,字典数据结构fromtypingimportListfromcollectionsimportCoun...