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9f2df60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 | """Property extraction strategy for programme classification."""
def run(file_name: str, file_content: str, chunk: str) -> list[str]:
"""
Classify a chunk into one or more Executive MBA programme buckets.
Scoring:
- programme signal in the page address/path: +2.0
- programme signal in the chunk: +1.0
- programme signal in the whole document: +0.5 per occurrence
The shared ``emba.unisg.ch`` host is not counted as an EMBA HSG signal;
otherwise every shared admissions page would be biased toward ``emba``.
"""
import re
from collections import Counter
from urllib.parse import urlparse
programmes = ("emba", "iemba", "emba_x")
scores = Counter({programme: 0.0 for programme in programmes})
address_text = _address_text(file_name, urlparse, re)
chunk_text = chunk or ""
document_text = file_content or ""
shared_requirements = _is_shared_emba_iemba_requirements(chunk_text)
if shared_requirements and _is_embax_redirect_only(chunk_text):
return ["emba", "iemba"]
if shared_requirements:
scores["emba"] += 1.0
scores["iemba"] += 1.0
for programme in programmes:
if _contains_programme_signal(address_text, programme, re):
scores[programme] += 2.0
if _contains_programme_signal(chunk_text, programme, re):
scores[programme] += 1.0
scores[programme] += 0.5 * _count_programme_signals(document_text, programme, re)
positive_scores = {
programme: score
for programme, score in scores.items()
if score > 0
}
if not positive_scores:
return []
max_score = max(positive_scores.values())
threshold = max(1.0, max_score - 0.5)
return [
programme
for programme in programmes
if positive_scores.get(programme, 0.0) >= threshold
]
def _address_text(file_name: str, urlparse, re) -> str:
address = (file_name or "").lower()
parsed = urlparse(address)
if parsed.scheme and parsed.netloc:
host = parsed.netloc
path = parsed.path
# emba.unisg.ch is the shared Executive MBA site, not the German EMBA
# programme itself. Keep programme-specific hosts such as embax.ch.
host_text = "" if host in {"emba.unisg.ch", "www.emba.unisg.ch"} else host
return f"{host_text} {path}".replace("-", " ").replace("_", " ")
# Local extracted filenames often start with the shared host prefix.
address = re.sub(r"^emba[-_]unisg[-_]ch[-_]?", "", address)
return address.replace("-", " ").replace("_", " ")
def _contains_programme_signal(text: str, programme: str, re) -> bool:
return _count_programme_signals(text, programme, re) > 0
def _count_programme_signals(text: str, programme: str, re) -> int:
text = text or ""
patterns = {
"emba_x": [
r"\bemba\s*x\d*\b",
r"\bembax\b",
r"\bemba\s+eth\s+hsg\b",
r"\bemba\s+eth\s+zurich\s*\+\s*university\s+of\s+st\.?gallen\b",
],
"iemba": [
r"\biemba(?:\s+hsg)?\b",
r"\binternational\s+emba(?:\s+hsg)?\b",
r"\binternational\s+executive\s+mba(?:\s+hsg)?\b",
],
"emba": [
r"(?<!international\s)\bemba\s+hsg\b",
r"(?<!international\s)\bexecutive\s+mba\s+hsg\b(?!\s+programmes\b|\s+programs\b)",
r"\bemba\s+\d{2}\b",
r"\bgerman[-\s]speaking\s+programme\b",
r"\bgerman[-\s]speaking\s+program\b",
],
}
return sum(
len(re.findall(pattern, text, flags=re.IGNORECASE))
for pattern in patterns.get(programme, [])
)
def _is_shared_emba_iemba_requirements(text: str) -> bool:
text_lower = (text or "").lower()
return (
"application requirements" in text_lower
and "executive mba hsg programmes" in text_lower
and "minimum 5 years" in text_lower
and "minimum 3 years" in text_lower
)
def _is_embax_redirect_only(text: str) -> bool:
text_lower = (text or "").lower()
return (
"for emba x programme application requirements click" in text_lower
or "for emba x program application requirements click" in text_lower
)
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