Generate Tag for Video Caption solution and explanation
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The problem
You are given a string caption representing the caption for a video.
The following actions must be performed in order to generate a valid tag for the video:
-
Combine all words in the string into a single camelCase string prefixed with
'#'. A camelCase string is one where the first letter of all words except the first one is capitalized. All characters after the first character in each word must be lowercase. -
Remove all characters that are not an English letter, except the first
'#'. -
Truncate the result to a maximum of 100 characters.
Return the tag after performing the actions on caption.
Example 1:
Input: caption = "Leetcode daily streak achieved"
Output: "#leetcodeDailyStreakAchieved"
Explanation:
The first letter for all words except "leetcode" should be capitalized.
Example 2:
Input: caption = "can I Go There"
Output: "#canIGoThere"
Explanation:
The first letter for all words except "can" should be capitalized.
Example 3:
Input: caption = "hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh"
Output: "#hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh"
Explanation:
Since the first word has length 101, we need to truncate the last two letters from the word.
Constraints:
1 <= caption.length <= 150captionconsists only of English letters and' '.
Approach overview
Problem Overview: You receive a video caption as a string and must generate a valid tag from it. The task mainly involves scanning the caption, transforming words into a tag-style format, and constructing the final string using simple string operations.
Approach 1: Basic Simulation with Word Processing (O(n) time, O(n) space)
The straightforward solution is to simulate the tag creation process step by step. Split the caption into words using spaces, then process each word while building the result string. Typically the first word stays lowercase while the following words start with an uppercase letter to form a camelCase style tag. Each processed word is appended to the result, usually prefixed with a #.
This approach relies on standard string manipulation such as split, lower(), upper(), and concatenation. Since every character in the caption is processed at most once, the overall time complexity is O(n) where n is the caption length. The constructed tag also requires O(n) space.
Approach 2: Single-Pass Character Simulation (O(n) time, O(n) space)
A more direct method avoids splitting the string and instead iterates through the caption character by character. Track whether the current character starts a new word. When a new word begins, capitalize the first character (except possibly the first word) and append it to the output string. Skip unnecessary separators such as spaces and continue copying valid characters.
This technique is still a simulation but reduces intermediate allocations because you build the result while scanning the original string. Every character is visited once, giving O(n) time complexity and O(n) space for the generated tag. This pattern frequently appears in string formatting problems and basic simulation tasks.
Recommended for interviews: The single-pass simulation is the expected solution. It demonstrates control over string traversal and edge cases such as multiple spaces or formatting rules. The split-based approach is still valid and easier to write quickly, but the single-pass version shows stronger implementation skills with string processing.
Solution
We first split the title string into words, then process each word. The first word should be all lowercase, while for the subsequent words, the first letter is capitalized and the rest are lowercase. Next, we concatenate all the processed words and add a # symbol at the beginning. Finally, if the generated tag exceeds 100 characters in length, we truncate it to the first 100 characters.
The time complexity is O(n), and the space complexity is O(n), where n is the length of the title string.
class Solution:
def generateTag(self, caption: str) -> str:
words = [s.capitalize() for s in caption.split()]
if words:
words[0] = words[0].lower()
return "#" + "".join(words)[:99]class Solution {
public String generateTag(String caption) {
String[] words = caption.trim().split("\\s+");
StringBuilder sb = new StringBuilder("#");
for (int i = 0; i < words.length; i++) {
String word = words[i];
if (word.isEmpty()) {
continue;
}
word = word.toLowerCase();
if (i == 0) {
sb.append(word);
} else {
sb.append(Character.toUpperCase(word.charAt(0)));
if (word.length() > 1) {
sb.append(word.substring(1));
}
}
if (sb.length() >= 100) {
break;
}
}
return sb.length() > 100 ? sb.substring(0, 100) : sb.toString();
}
}class Solution {
public:
string generateTag(string caption) {
istringstream iss(caption);
string word;
ostringstream oss;
oss << "#";
bool first = true;
while (iss >> word) {
transform(word.begin(), word.end(), word.begin(), ::tolower);
if (first) {
oss << word;
first = false;
} else {
word[0] = toupper(word[0]);
oss << word;
}
if (oss.str().length() >= 100) {
break;
}
}
string ans = oss.str();
if (ans.length() > 100) {
ans = ans.substr(0, 100);
}
return ans;
}
};function generateTag(caption: string): string {
const words = caption.trim().split(/\s+/);
let ans = '#';
for (let i = 0; i < words.length; i++) {
const word = words[i].toLowerCase();
if (i === 0) {
ans += word;
} else {
ans += word.charAt(0).toUpperCase() + word.slice(1);
}
if (ans.length >= 100) {
ans = ans.slice(0, 100);
break;
}
}
return ans;
}func generateTag(caption string) string {
words := strings.Fields(caption)
var builder strings.Builder
builder.WriteString("#")
for i, word := range words {
word = strings.ToLower(word)
if i == 0 {
builder.WriteString(word)
} else {
runes := []rune(word)
if len(runes) > 0 {
runes[0] = unicode.ToUpper(runes[0])
}
builder.WriteString(string(runes))
}
if builder.Len() >= 100 {
break
}
}
ans := builder.String()
if len(ans) > 100 {
ans = ans[:100]
}
return ans
}Complexity analysis
| Approach | Time | Space | When to Use |
|---|---|---|---|
| Word Split Simulation | O(n) | O(n) | Quick implementation when built-in string split and formatting functions are allowed |
| Single-Pass Character Simulation | O(n) | O(n) | Preferred approach in interviews for precise control over string parsing |
Frequently asked questions
Is Generate Tag for Video Caption easy or hard?
Generate Tag for Video Caption is considered an Easy problem. The challenge mainly involves careful string traversal and formatting rules rather than complex data structures or algorithms.
Generate Tag for Video Caption Python/Java solution
Python and Java implementations both follow the same simulation logic. Traverse the caption, detect word boundaries, adjust capitalization, and append characters to a result string or StringBuilder. The algorithm remains O(n) in both languages.
How to solve Generate Tag for Video Caption in O(n)?
Iterate through the caption once and track when a new word begins. Append characters to the result while adjusting the first letter of each word to match the required tag format. Because each character is visited only once, the algorithm achieves O(n) time complexity.
What is the best approach for Generate Tag for Video Caption?
The best approach is a single-pass simulation that scans the caption character by character and builds the tag string directly. It formats each word appropriately while skipping spaces and separators. This runs in O(n) time and uses O(n) space for the final tag.
Is Generate Tag for Video Caption asked at Google/Amazon/Meta?
String formatting and simulation problems like this frequently appear in interviews at companies such as Google, Amazon, and Meta. While the exact problem may vary, tasks involving string parsing, capitalization rules, and tag generation are common practice questions.
What data structure is used in Generate Tag for Video Caption?
The problem mainly uses basic string manipulation. Most solutions build the result using a string builder or dynamic string while iterating through the input caption.
What is the time complexity of Generate Tag for Video Caption?
The optimal solution runs in O(n) time where n is the length of the caption. Each character is processed once while constructing the resulting tag. Space complexity is O(n) because a new formatted string is created.