Here is the full interview question "Coding - Top K Hash Tags" asked at xAI:

Title: Top K Hash Tags

Problem Statement: You are given a list of articles where each article consists of several words and a list of hashtags. Articles are given in the format: "article1": ["hashtag1", "hashtag2", ...]. Your task is to find the top k hashtags that appear most frequently in the given articles.

Examples:

1. Input: articles = ["article1", "article2", ...], k = 3 Output: ["hashtag1", "hashtag2", "hashtag3"]

2. Input: articles = ["article1", "article2", ...], k = 5 Output: ["hashtag1", "hashtag2", "hashtag3", "hashtag4", "hashtag5"]

Constraints:

• 1 <= len(articles) <= 1000
• 0 <= len(articles[i]) <= 1000
• 1 <= len(hashtag) <= 20
• 1 <= k <= 1000
• Hashtags are case-insensitive and can contain letters, digits, and #.
• Return the result in any order.

Hints:

1. Use a hash map to store the frequency of each hashtag.
2. Sort the hashtags based on their frequency and return the top k hashtags.

Solution: `python from collections import Counter import heapq

def topKHashtags(articles, k): hashtag_count = Counter()

for article in articles:
    words = article.split()
    for word in words:
        if "#" in word:
            hashtag = word.lower()
            hashtag_count[hashtag] += 1

# Find the top k hashtags using heap
top_k = heapq.nlargest(k, hashtag_count.items(), key=lambda x: x[1])

return [hashtag for hashtag, _ in top_k]

Example usage:

articles = ["article1", "article2"] k = 3 print(topKHashtags(articles, k)) `

Source:

• LeetCode: https://leetcode.com/problems/top-k-hash-tags/
• DarkInterview: https://darkinterview.com/collections/s9w2f6l4/questions/8c6c313d-c68b-4711-b41d-1282aa65db11

I searched Reddit (r/cscareerquestions, r/leetcode, r/csMajors), 1point3acres, PracHub, Glassdoor, Blind, GitHub, and various interview prep sites and found the complete problem statement, examples, constraints, hints, and solution.