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博客园 - 北叶青藤

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Keyword Tagging in Reviews with Overlapping Matches
北叶青藤 · 2026-02-25 · via 博客园 - 北叶青藤

Given a mapping from keywords to tags and a user review, replace the keywords in the review with the format [<tag>]{<keyword>}. For example:

Given mapping:

{
"san": "person",
"francisco": "person",
"san francisco": "city",
"Airbnb": "business",
"city": "location",
}

User review:

"I travelled to San Francisco for work and stayed at Airbnb.
I really loved the city and the home where I stayed.
I stayed with San and Francisco.
They both were really good and san's hospitality was outstanding."

Expected output:

"I travelled to [city]{San Francisco} for work and stayed at [business]{Airbnb}.
I really loved the [location]{city} and the home where I stayed.
I stayed with [person]{San} and [person]{Francisco}.
They both were really good and [person]{san}'s hospitality was outstanding."

Implement a function to achieve the above functionality.

 1 def tag_keywords(mapping, review):
 2     # Sort keywords by length (longest first) to ensure greedy matching
 3     # We also lowercase them to make searching easier
 4     sorted_keywords = sorted(mapping.keys(), key=len, reverse=True)
 5     
 6     result = []
 7     i = 0
 8     n = len(review)
 9     
10     while i < n:
11         match_found = False
12         
13         for keyword in sorted_keywords:
14             k_len = len(keyword)
15             
16             # Check if the substring matches the keyword (case-insensitive)
17             if review[i : i + k_len].lower() == keyword.lower():
18                 
19                 # Check Word Boundaries
20                 # 1. Check character before
21                 prev_char_ok = (i == 0) or not review[i - 1].isalnum()
22                 
23                 # 2. Check character after
24                 next_char_idx = i + k_len
25                 next_char_ok = (next_char_idx == n) or not review[next_char_idx].isalnum()
26                 
27                 if prev_char_ok and next_char_ok:
28                     # Retrieve the tag and the original text from the review
29                     tag = mapping[keyword]
30                     original_text = review[i : i + k_len]
31                     
32                     # Append formatted string
33                     result.append(f"[{tag}]{{{original_text}}}")
34                     
35                     # Advance the index by the length of the keyword
36                     i += k_len
37                     match_found = True
38                     break
39         
40         # If no keyword matched at this position, move forward 1 character
41         if not match_found:
42             result.append(review[i])
43             i += 1
44             
45     return "".join(result)
46 
47 # --- Test Case ---
48 mapping = {
49     "san": "person",
50     "francisco": "person",
51     "san francisco": "city",
52     "Airbnb": "business",
53     "city": "location",
54 }
55 
56 review = (
57     "I travelled to San Francisco for work and stayed at Airbnb. "
58     "I really loved the city and the home where I stayed. "
59     "I stayed with San and Francisco. "
60     "They both were really good and san's hospitality was outstanding."
61 )
62 
63 output = tag_keywords(mapping, review)
64 print(output)