import re
text = "The title of the resource is: 'Nova Resource Title Function'"
pattern = r"('(.+?)'|\"(.+?)\")"  # Matches text enclosed in single or double quotes
matches = re.findall(pattern, text)
title = matches[0][1] if matches else None
print(title)  # Output: Nova Resource Title Function

from bs4 import BeautifulSoup
html = "<title>Nova Resource Title Function</title>"
soup = BeautifulSoup(html, "html.parser")
title = soup.title.string if soup.title else None
print(title)  # Output: Nova Resource Title Function

from sklearn.linear_model import LinearRegression
# X: Input features (e.g., text, metadata)
X = [...]  # Your input data
# y: Target variable (resource titles)
y = [...]  # Your target data
model = LinearRegression()
model.fit(X, y)
# Given a new input `text`, predict the title
text = "The resource is titled 'Nova Resource Title Function'"
predicted_title = model.predict([text])
print(predicted_title)  # Output: Nova Resource Title Function