Files
odysseus/services/search/ranking.py
Afonso Coutinho b55c970ec5 fix: sports-hint ranking penalty fires on 'transport'/'passport' substrings (#1473)
* fix: sports-hint ranking penalty fires on 'transport'/'passport' substrings

* Apply word-boundary sports-hint fix to src/search/ranking.py as well
2026-06-03 14:23:52 +09:00

133 lines
4.8 KiB
Python

"""Search result ranking based on relevance, source quality, and recency."""
import re
import logging
from datetime import datetime
from typing import List, Optional
from urllib.parse import urlparse
logger = logging.getLogger(__name__)
_NEWS_HINTS = {"news", "nyheter", "headlines", "breaking", "latest", "today", "idag"}
_SPORTS_HINTS = {
"sport", "sports", "soccer", "football", "hockey", "nba", "nfl", "mlb",
"fifa", "world cup", "championship", "quarterfinal", "eliminates",
}
# Word-boundary match so "sport" does not fire inside "transport"/"passport"
# and a domain like "transport.gov" is not mistaken for a sports site.
_SPORTS_HINT_RE = re.compile(
r"\b(?:" + "|".join(re.escape(h) for h in _SPORTS_HINTS) + r")\b"
)
_LOW_VALUE_NEWS_DOMAINS = {
"facebook.com", "www.facebook.com", "sports.yahoo.com", "yahoo.com",
"www.yahoo.com", "msn.com", "www.msn.com",
}
_TRUSTED_NEWS_DOMAINS = {
"apnews.com", "www.apnews.com", "reuters.com", "www.reuters.com",
"bbc.com", "www.bbc.com", "cbc.ca", "www.cbc.ca",
"ctvnews.ca", "www.ctvnews.ca", "globalnews.ca", "www.globalnews.ca",
"theguardian.com",
"www.theguardian.com", "euronews.com", "www.euronews.com",
"dw.com", "www.dw.com", "government.se", "www.government.se",
}
def _domain(url: str) -> str:
try:
return urlparse(url).netloc.lower()
except Exception:
return ""
def rank_search_results(query: str, results: List[dict]) -> List[dict]:
"""Rank search results by title relevance, snippet quality, domain authority, and recency."""
query_terms = [t.lower() for t in re.findall(r"\b\w+\b", query)]
query_lc = query.lower()
is_news_query = any(term in _NEWS_HINTS for term in query_terms)
is_sports_query = bool(_SPORTS_HINT_RE.search(query_lc))
def title_score(title: str) -> float:
if not title:
return 0.0
title_lc = title.lower()
matches = sum(1 for term in query_terms if re.search(rf"\b{re.escape(term)}\b", title_lc))
return matches / len(query_terms) if query_terms else 0.0
def snippet_score(snippet: str) -> float:
if not snippet:
return 0.0
length_factor = min(len(snippet), 200) / 200
term_hits = sum(1 for term in query_terms if term in snippet.lower())
term_factor = term_hits / len(query_terms) if query_terms else 0.0
return (length_factor + term_factor) / 2
def domain_score(url: str) -> float:
netloc = _domain(url)
if not netloc:
return 0.0
if netloc in _TRUSTED_NEWS_DOMAINS:
return 1.0
if netloc.endswith(".edu") or netloc.endswith(".gov"):
return 1.0
if netloc.endswith(".org"):
return 0.7
return 0.4
def recency_score(age_str: Optional[str]) -> float:
if not age_str:
return 0.0
for fmt in ("%Y-%m-%d", "%Y-%m-%dT%H:%M:%S", "%Y-%m-%d %H:%M:%S"):
try:
dt = datetime.strptime(age_str, fmt)
break
except Exception:
dt = None
if not dt:
return 0.0
days_old = (datetime.now() - dt).days
if days_old <= 7:
return 1.0
if days_old >= 30:
return 0.0
return (30 - days_old) / 23
def news_quality_adjustment(title: str, snippet: str, url: str) -> float:
if not is_news_query:
return 0.0
text = f"{title} {snippet}".lower()
netloc = _domain(url)
adjustment = 0.0
if netloc in _TRUSTED_NEWS_DOMAINS:
adjustment += 1.2
if any(term in text for term in ("latest news", "breaking news", "daily coverage", "news from")):
adjustment += 0.4
if netloc in _LOW_VALUE_NEWS_DOMAINS:
adjustment -= 0.8
if not is_sports_query and (_SPORTS_HINT_RE.search(text) or _SPORTS_HINT_RE.search(netloc)):
adjustment -= 1.5
# A country/news query should not rank a page whose title/snippet barely
# mentions the country above actual news pages for that country.
subject_terms = [t for t in query_terms if t not in _NEWS_HINTS]
if subject_terms and not any(t in text or t in netloc for t in subject_terms):
adjustment -= 1.0
return adjustment
ranked = []
for result in results:
title = result.get("title", "")
snippet = result.get("snippet", "")
url = result.get("url", "")
age = result.get("age", None)
score = (
2.0 * title_score(title)
+ 1.0 * snippet_score(snippet)
+ 1.5 * domain_score(url)
+ 1.0 * recency_score(age)
+ news_quality_adjustment(title, snippet, url)
)
ranked.append((score, result))
ranked.sort(key=lambda x: x[0], reverse=True)
return [r for _, r in ranked]