Given a list of words, you need to encode these words by using the shortest reference string and a list of indices. The reference string should be composed of all the words concatenated together with ‘#’ as the delimiter between words. The goal is to find the shortest possible reference string that can encode all the words.
To minimize the length of the encoding string, we can leverage suffixes. If one word is a suffix of another, we can avoid encoding it separately.
#
character).By the end of this process, the length of the encoding string will be our answer.
The time complexity is approximately (O(N \cdot L^2)), where (N) is the number of words and (L) is the maximum length of the words. This is because for each word, we may need to add all suffixes (up to L operations per word), and checking membership in the set is (O(1)) on average.
Here’s the Python implementation of the described strategy:
def minimumLengthEncoding(words):
# Sort words by length in descending order
words.sort(key=len, reverse=True)
# Initialize set to keep track of suffixes
unique_suffixes = set()
# Result length
encoding_length = 0
# Iterate over each word
for word in words:
if word not in unique_suffixes:
# If word is not in suffixes, add all its suffixes to the set
for i in range(len(word)):
unique_suffixes.add(word[i:])
# Increase the encoding length by this word length + 1 for the '#'
encoding_length += len(word) + 1
return encoding_length
# Example usage:
words = ["time", "me", "bell"]
print(minimumLengthEncoding(words)) # Output: 10
In the example, [“time”, “me”, “bell”]:
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