Keyword ExtractorName
Kushandiswa kwekutengesa OK
380 + mamodheru
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Hapana kumbobvira kushanyira
Model:
+ GPT-5, Claude, Gemini
_Zvirongwa
Chikamu
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Kugadzirisa yako mibvunzo...
Kubvisa mazwi akakosha kubva kune chero chinyorwa nemahara AI. SEO uye ongororo yemukati yakapusa.
Maitiro ekuisa Keyword ExtractorName
1
Sarudza yako input
Tinya meseji, wedzera faira, kana kuti nyora zvaunoda. Hapana account yaunoda.
2
Tinya kuumba
Our AI inoongorora yako mibvunzo mumasekondi nekushandisa yakanakisa open-source mamodheru.
3
Dhawunirodha & shandisa
Dhawunirodha, kopa kana kugovera yako mhinduro. Yemahara yemunhu uye yekutengesa kushandiswa.
Usashandisa iyi chirongwa kuburikidza neAPI
Automatize iyi chirongwa kubva yako pachako code. OpenAI-inowirirana REST endpoint, Bearer-token auth, hapana zvishoma SDK zvinodiwa. Token mutengo kusangana web interface.
curl -X POST https://api.free.ai/v1/chat/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model": "qwen7b", "messages": [{"role": "user", "content": "Summarize this: ..."}]}'Zvinoenderana neFree AI Tools
Keyword ExtractorName — FAQ
Kubvisa mazwi uye mazwi ane chekuita kubva kune chero fomu-refu rezita (chinyorwa, blog post, transcript, chirevo cheprodukt). Maviri ekugadzirisa modhi: (1) SEO keywords nekutsvaga-chinangwa tagging, (2) makuru-level topics + themes, (3) anozivikanwa entities — vanhu / nzvimbo / sangano, (4) tag-style smallcase-hyphen-joined tags, (5) akateedzana index terms. Results scored 0-100 by TF-IDF, raw frequency, or semantic relevance. Export as CSV, TXT, or JSON.
Yeah — a 1,500-word article extracts in ~350 tokens on the default Qwen 3 30B model, comfortably inside the 2,500 anonymous or 10,000 signed-up daily pool. No sign-up required for your first extraction.
Izvo zvinoshandiswa zvinotora live search-volume data yemazwi akakosha iwe unovapa ($ 99 + / mo). Iyi chirongwa inoita zvakasiyana - inotora mazwi akakosha evavhoti kubva kune yako saiti uye inoenzanisa kutsvaga kwavari. Workflow: shandisa izvi kuti uwane izvo mashoko ako achangobva kukurudzira, wozoisa iwo muAhrefs / Semrush kuti uone mwedzi wega wega wekutsvaga.
Three scoring modes: (1) TF-IDF (default) anopa mashoko vaviri zvakajairika muichi chinyorwa uye rakakura muEnglish — zvakanaka kwazvo SEO sezvo izvi vari kuchinja zvirevo. (2) Raw frequency inofungidzira zviitiko straight — zvakanaka kana iwe uchida kuona kuti chii iwe mashoko zvikuru. (3) Semantic relevance scores by proximity to the documents main thesis even if a phrase appears only once — best for topical coherence.
An n-gram imwechete tevera N mazwi. "kuchinja kwekunze" i 2-gram. "artificial intelligence model" i 3-gram. Toggle the chips to extract only 1-grams (single words like "photosynthesis"), 2-grams (head phrases like "carbon footprint"), or 3-grams (long-tail like "carbon footprint calculator"). Most SEO workflows want 2 + 3-grams - single words are too generic.
Yes — the default stoplist removes "the", "and", "of", "is", etc. in 14 languages. You can add custom stopwords via the "Words to exclude" field — useful for suppressing your own brand name, product codes, or boilerplate legalese that would otherwise dominate the results.
Google inoparadzira mibvunzo nechinangwa chemushandisi: chinopa ruzivo ("izvi ndezvipi X"), chinopa ruzivo rwekufambisa ("nike official store"), chinopa ruzivo rwekutengeserana ("best running shoes 2026"), chinopa ruzivo rwekutenga ("buy air max online"). Chigadzirwa ichi chinobata mazwi ako akagadzirwa nechinangwa chaungade kuti uzive kana chinyorwa chako chinofanira kunyorwa kune vanotsvakurudza, vatengesi kana kuongororwa kwenzvimbo dzevafambi.
99 languages via the underlying Qwen 2.5 model. Highest quality on English, Spanish, French, Portuguese, German, Chinese, Japanese. Lower-source languages work but 3-gram extraction may be less reliable — fall back to 1+2-grams for Arabic, Hindi, Turkish, etc.
The UI runs one text at a time. For bulk extraction wire the /v1/chat/ API into a Python script — iterate over your CMS export, POST each article body, dump the JSON. Bearer auth, 1,000 calls/hour on free accounts, higher limits on pro. Docs at /api/.
RAKE uye YAKE ndezvekare lexical algorithms - nekukurumidza asi zvakaipa pa semantic nuance (vanoda "tech startup" kana iyo dokumendi ichiti "technology startup" asi kwete "tech" chete). KeyBERT inoshandisa BERT embeddings - yakanaka semantic mhando asi yakaderera uye inodiwa kuiswa. TextRank inoenderana negraph. Isu tinoshandisa 7B-parameter LLM iyo inoita zvese zvakapfuura zero-shot plus search-intent classification - yakaderera pafoni asi zero setup, yemahara, uye hapana ML engineering inodiwa.
Mu frequency uye TF-IDF modes, hapana — chero keyword inobva pakutanga kwechinyorwa kana nekuwedzera-kuwedzera kwakaderera. Mu semantic-relevance mode, iyo model inogona kudzosa yakadzorwa-vocabulary vhezheni ("pulmonology" kunyange kana yako chinyorwa ichiti "lung doctor visit").
Yeah — POST to /v1/chat/ with the same system prompt this page builds (inspect template source for the exact prompt). Returns structured JSON. Good for content-strategy dashboards or CMS plugins. Bearer auth, monthly limits. Docs at /api/.
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