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N-gram (Bigram / Trigram) Analyzer

किसी भी टेक्स्ट में सबसे आम बाइग्राम, ट्राइग्राम, 4-ग्राम या 5-ग्राम निकालें। न्यूनतम आवृत्ति से फ़िल्टर करें।

कब उपयोग करें

Use the n-gram analyzer to find common phrases in writing, transcripts, or scraped content. Especially useful for SEO topical analysis, content gap analysis, and discovering author voice patterns.

तुलना

The n-gram analyzer is more general than Keyword Density (no SEO framing). It's the natural next step after Word Frequency if you suspect important phrases lie above the single-word level.

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यह कैसे काम करता है

An n-gram is a contiguous sequence of n words from a text. Bigrams are 2-word sequences ("machine learning"); trigrams are 3-word ("artificial neural network").

The analyzer counts every n-gram, filters by minimum frequency, and optionally drops phrases composed entirely of stopwords.

Lowercase normalization treats "The Cat" and "the cat" as the same n-gram — usually what you want for analysis.

अक्सर पूछे जाने वाले प्रश्न

What's the difference between this and keyword density?

Keyword density adds percentages and over-optimization warnings for SEO. The n-gram analyzer is a general phrase-frequency tool without the SEO framing.

Why drop pure-stopword phrases?

Without filtering, the top n-grams are always "of the", "in the", "to the" — uninformative. The filter drops phrases composed entirely of stopwords.

When should I use n=4 or n=5?

For finding repeated long phrases — quotes, slogans, boilerplate. Most useful n is 2 or 3.

व्यावहारिक उदाहरण

इनपुट

500-word product description.

आउटपुट

Top bigrams: "machine learning" (8), "neural network" (5), "training data" (4).

N-grams reveal the actual phrases that dominate a text, including phrases the writer didn't consciously target. Useful for SEO topic discovery and content audit.

सामान्य गलतियाँ

  • Without the stopword purge filter, top n-grams will be filled with "of the", "in the", "and the".
  • Short texts (<200 words) rarely produce stable n-grams.
  • Phrasal verbs and idioms span 2–3 words — n=2 and n=3 catch different things.
  • Hapax phrases (appearing once) flood the results — set min frequency ≥ 2.

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