#tfidf
Live, measured metrics for the hashtag #tfidf from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #tfidf
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 06:47 UTC2 uses by 1 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 06:47 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 06:47 UTCEverything below is measured over the latest 31 public posts (spanning ~56802 hours).
Posting hours (UTC) — busiest: 07:00
Languages: English (15) · Russian (10) · Polish (4) · Japanese (2)
Avg boosts / post: 0.4
Top of the latest posts
planning for #CfgMgmtCamp ? Not sure what track(s) to attend? I have you covered! Behold, my entirely hacky TF-IDF analysis of the talk submissions, broken down by room & day. In other words, what words are common to each room *specifically
How a computer reads text - from counting words to vectors From tokenization through TF-IDF and Markov chains, to Word2Vec. How a computer turns text into numb... https://gruszka.dev/en/how-computer-reads-text.html #llm #ai #nlp #tokenizati
Jak komputer czyta tekst - od liczenia słów do wektorów Od tokenizacji przez TF-IDF i łańcuchy Markowa, aż po Word2Vec. Jak komputer zamienia tekst w liczby... https://gruszka.dev/jak-komputer-czyta-tekst.html #llm #ai #nlp #tokenizacja #wo
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/tfidf