Term Frequencies
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Term Frequencies has 5 facts recorded in Dontopedia across 2 references.
5 facts·5 predicates·2 sources
Mostly:stores(1), computed from(1), rdf:type(1)
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Term Frequencies has 5 facts recorded in Dontopedia across 2 references.
Mostly:stores(1), computed from(1), rdf:type(1)
rdfs:labelOther 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.
returnsReturns(1)ex:calculate_term_frequenciestakesParameterTakes Parameter(1)ex:printTimeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/6754c089-a9ba-4d68-a4bf-7f175c66d000- If you are dealing with very large datasets, consider using vectorized operations provided by libraries like `numpy` or `pandas`. ### Example with Profiling Here's how you can profile the code to identify bottlenecks: ```python impo…
doc:beam/c0f00081-8803-4769-b3dc-7642832fcf0a["term1", "term2", "term3"], ["term2", "term3", "term4"], ["term1", "term2", "term3", "term4"] ] # Calculate the term frequencies term_frequencies = calculate_term_frequencies(documents) print(term_frequencies) ``` ### Explana…
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