博客
关于我
LeetCode Most Common Word 最常见的词
阅读量:803 次
发布时间:2023-01-31

本文共 3035 字,大约阅读时间需要 10 分钟。

Here is an optimized version of the thought process and solution:

  • Data Preparation

    • Convert the entire paragraph to lowercase to handle case insensitivity.
    • Remove all punctuation marks (such as commas, periods, exclamation points, etc.) to isolate words.
    • Ensure words are properly separated by spaces to avoid partial words (e.g., "ball," becomes "ball").
  • Word Frequency Calculation

    • Traverse the prepared string, extracting each word by ignoring punctuation and case differences.
    • Use a hash map (dictionary) to count occurrences of each word.
    • For each character in the paragraph: If it's a letter, add it to the current word being built. If it's not a letter or reaches the end of the string, finalize the word and update its count in the hash map.
  • Filter Banned Words

    • Store banned words in a set for quick lookup.
    • Iterate through the hash map to exclude any words that exist in the banned set, keeping only valid words.
  • Determine Most Frequent Word

    • Sort the remaining words by their frequency in descending order.
    • Return the first word in this sorted list, as it by definition is unique and has the highest count according to the problem constraints.
  • Final Solution Code

    import java.util.HashMap;import java.util.HashSet;import java.util.Map;public class Solution {    public String mostCommonWord(String paragraph, String[] banned) {        // Convert paragraph to lowercase and remove punctuation        StringBuilder cleanParagraph = new StringBuilder();        for (char c : paragraph.toCharArray()) {            if (c >= 'a' && c <= 'z') {                cleanParagraph.append(c);            }        }        // Split into words        String[] words = cleanParagraph.toString().split(" +");        // Count frequency of each word        Map
    frequencyMap = new HashMap<>(); for (String word : words) { frequencyMap.put(word, frequencyMap.getOrDefault(word, 0) + 1); } // Create banned words set for quick lookup HashSet
    bannedWords = new HashSet<>(); for (String bw : banned) { bannedWords.add(bw.toLowerCase()); } // Exclude banned words and find the most frequent int maxCount = -1; String result = ""; for (Map.Entry
    entry : frequencyMap.entrySet()) { if (!bannedWords.contains(entry.getKey())) { if (entry.getValue() > maxCount) { maxCount = entry.getValue(); result = entry.getKey(); } } } return result; }}

    Explanation

    • The code first processes the input paragraph to remove punctuation and convert it to lowercase, ensuring uniformity in word processing.
    • It then splits the cleaned string into individual words and uses a hash map to count each word's occurrences.
    • Banned words are stored in a set for quick exclusion.
    • Finally, the code iterates through the frequency map, excluding banned words, and identifies the word with the highest count, which is then returned as the result.

    转载地址:http://oogyk.baihongyu.com/

    你可能感兴趣的文章
    PHP获取当前文件的绝对路径
    查看>>
    PHP获取当前时间、时间戳的各种格式写法汇总
    查看>>
    PHP获取当前页面的完整URL
    查看>>
    php获取数据库中数据生成json,中文乱码问题的解决方案
    查看>>
    php获取文件夹中文件的两种方法
    查看>>
    PHP获取日期的一些方法总结
    查看>>
    R2学习记录
    查看>>
    PHP获取本周的每一天的时间
    查看>>
    php获取用户真实IP和防刷机制
    查看>>
    php获取网页内容的三种方法
    查看>>
    R-CNN算法优化策略
    查看>>
    PHP规范PSR0和PSR4的理解
    查看>>
    php解析ipa包,获取logo
    查看>>
    R&Rstudio安装各种包
    查看>>
    php设置cookie,在js中如何获取
    查看>>
    php设置socket超时时间
    查看>>
    php设计模式 萨莱 pdf,PHP设计模式 建造者模式
    查看>>
    PHP设计模式之----观察者模式
    查看>>
    php设计模式之装饰器模式
    查看>>
    R&Python Data Science系列:数据处理(5)--字符串函数基于R(一)
    查看>>