In this problem, you need to replace derivatives in a sentence with the shortest matching root from a dictionary. The approach involves scanning the sentence and looking up the roots in a hash table to find the shortest match for each word. The solution must efficiently handle large input sizes while ensuring correct replacements are made.
Problem Statement
Given a dictionary of root words and a sentence, you need to replace every word in the sentence that is a derivative of a root in the dictionary with its corresponding root. If a word can be formed from multiple roots, choose the root with the shortest length. Return the updated sentence after all replacements are made.
For example, for dictionary = ["cat", "bat", "rat"] and sentence = "the cattle was rattled by the battery", you should replace 'cattle' with 'cat', 'rattled' with 'rat', and 'battery' with 'bat', resulting in the sentence "the cat was rat by the bat".
Examples
Example 1
Input: dictionary = ["cat","bat","rat"], sentence = "the cattle was rattled by the battery"
Output: "the cat was rat by the bat"
Example details omitted.
Example 2
Input: dictionary = ["a","b","c"], sentence = "aadsfasf absbs bbab cadsfafs"
Output: "a a b c"
Example details omitted.
Constraints
- 1 <= dictionary.length <= 1000
- 1 <= dictionary[i].length <= 100
- dictionary[i] consists of only lower-case letters.
- 1 <= sentence.length <= 106
- sentence consists of only lower-case letters and spaces.
- The number of words in sentence is in the range [1, 1000]
- The length of each word in sentence is in the range [1, 1000]
- Every two consecutive words in sentence will be separated by exactly one space.
- sentence does not have leading or trailing spaces.
Solution Approach
Array Scanning
The solution starts by scanning through each word in the sentence. For each word, check if it starts with any root from the dictionary. This can be efficiently done by iterating through the dictionary and finding the shortest match for each word.
Hash Table Lookup
Using a hash table or trie, you can store the roots for quick lookup. This helps in identifying the shortest root for each derivative word in the sentence. The hash table stores the roots as keys, enabling constant-time lookup for each word.
Efficient Replacement
Once the shortest root is found for a word, replace it in the sentence. Construct the final sentence by replacing all the words that have a matching root, ensuring the output sentence is correctly formatted with spaces.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | O(d \cdot w + s \cdot w) |
| Space | O(d \cdot w + s \cdot w) |
The time complexity is O(d * w + s * w), where d is the number of roots, w is the maximum length of a root, and s is the number of words in the sentence. The space complexity is also O(d * w + s * w), as we need to store the dictionary roots and process each word in the sentence for matching roots.
What Interviewers Usually Probe
- Tests understanding of efficient string matching and optimization techniques.
- Tests familiarity with hash tables and efficient lookup methods.
- Evaluates the ability to handle large input sizes and optimize for time and space complexity.
Common Pitfalls or Variants
Common pitfalls
- Overlooking edge cases such as words that have no matching root.
- Incorrectly handling cases where multiple roots can match, not picking the shortest.
- Not optimizing the search for roots, leading to slower solutions.
Follow-up variants
- Use a trie instead of a hash table to optimize root lookup.
- Limit the dictionary size or impose stricter constraints on the sentence.
- Allow multiple words to be replaced by multiple roots (e.g., handle word sequences).
How GhostInterview Helps
- GhostInterview helps by providing an optimized strategy for replacing words using hash lookup, minimizing processing time.
- It guides you through edge case handling to ensure your solution is robust and covers all potential word structures.
- GhostInterview helps optimize your approach by recommending best practices for handling large input sizes in both time and space.
Topic Pages
Related GhostInterview Pages
- LeetCode Interview Copilot - Use GhostInterview as a live solver when you want direct help with LeetCode-style coding questions.
- Coding Interview Assistant - See how GhostInterview supports array, string, linked list, graph, and tree interview workflows.
- How GhostInterview Works - Review the screenshot, reasoning, and answer flow before using the solver in a live interview.
FAQ
What is the main pattern for solving the Replace Words problem?
The main pattern involves array scanning combined with efficient hash table lookup to replace words in the sentence with their shortest root.
How can I optimize the replacement process for large sentences?
By using a hash table or trie to store the roots and performing a lookup for each word in the sentence, you can achieve efficient replacements even with large inputs.
What is the time complexity of the Replace Words problem?
The time complexity is O(d * w + s * w), where d is the number of dictionary words, w is the maximum length of a word, and s is the number of words in the sentence.
What if there are no matching roots for a word in the sentence?
If a word has no matching root, it remains unchanged in the sentence. Only words that can be replaced by a root are modified.
How can I handle multiple roots that match a word in the sentence?
You should always replace the word with the shortest root that matches it. This ensures that the solution meets the problem's requirements.
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