Inner Product
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
Inner Product has 3 facts recorded in Dontopedia across 1 reference.
Maturity scale
raw canonical shape-checked rule-derived certifiedRdf:typerdf:type
- Similarity Metric[1]all time · 3b1e0a95 Da47 45cb 81f4 B8a0f4b99a3c
Is Also CalledisAlsoCalled
- Cosine Similarity[1]sourceall time · 3b1e0a95 Da47 45cb 81f4 B8a0f4b99a3c
Is Equivalent toisEquivalentTo
- Cosine Similarity[1]sourceall time · 3b1e0a95 Da47 45cb 81f4 B8a0f4b99a3c
Inbound mentions (1)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
hasMetricHas Metric(1)
- Index
ex:index
Timeline
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References (1)
- custom
ctx:claims/beam/3b1e0a95-da47-45cb-81f4-b8a0f4b99a3c- full textbeam-chunktext/plain1 KB
doc:beam/3b1e0a95-da47-45cb-81f4-b8a0f4b99a3cShow excerpt
import numpy as np import faiss # Assuming I have a dataset of vectors vectors = np.random.rand(1000, 128).astype('float32') # Normalize the vectors for cosine similarity faiss.normalize_L2(vectors) # Build an index using FAISS index = f…
See also
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