# Learned ranking weights (generated offline by tools/ltr/train_rank_ltr.py)
# score = w_level*f_level + w_title*f_title + w_text*f_text
# Runtime can choose profile per host: [default], [blog], [docs], [ecommerce], [pdf_heavy].

[default]
w_level=0.52000000
w_title=0.20000000
w_text=0.28000000
std_level=0.08000000
std_title=0.05000000
std_text=0.07000000

[blog]
w_level=0.30000000
w_title=0.32000000
w_text=0.38000000
std_level=0.07000000
std_title=0.06000000
std_text=0.08000000

[ecommerce]
w_level=0.45000000
w_title=0.38000000
w_text=0.17000000
std_level=0.09000000
std_title=0.06000000
std_text=0.06000000

[docs]
w_level=0.36000000
w_title=0.16000000
w_text=0.48000000
std_level=0.07000000
std_title=0.04000000
std_text=0.08000000

[pdf_heavy]
w_level=0.42000000
w_title=0.13000000
w_text=0.45000000
std_level=0.08000000
std_title=0.04000000
std_text=0.09000000
