TF-IDF står for frekvens-inverse dokumentfrekvens, der bruges til at måle vigtigheden af et givet søgeord på en side. I modsætning til søgeordstæthed ser det ikke kun på antallet af gange, udtrykket bruges på siden; det analyserer også en større samling af sider og forsøger at bestemme, hvor vigtigt dette eller det søgeord er.
For eksempel, inden for bilreparation er udtrykket "dækreparation" sandsynligvis mere vigtigt end "reparation af turboopladet motor" - primært fordi hver bil har dæk, og kun et lille antal biler har turbo motorer. På grund af det vil udtrykket "dækreparation" blive brugt på en større samling af sider, der handler om bilreparation.
Dette er præcis det, som TF-IDF-rapporten i WebSite Audit vil kunne fange!
Ved at se på nøgleordsbrugsstatistikker fra et stort antal af dine konkurrenter vil TF-IDF-formlen vise dig:
Hvorfor bruge TF-IDF-rapporten?
Beregner faktorer for indholdsopdatering. Analyserer også, hvor godt din side er optimeret til dine målrettede søgeord.
Opdager de søgeord og sætningsudtryk, som dine top-rankede konkurrenter bruger
Find de ord og sætningsudtryk med anbefalinger om at bruge færre eller flere, så du kan justere din kopi for at forbedre relevansen
Hvordan fungerer TF-IDF-rapporten?
TF-IDF-rapporten fungerer ud fra en specifik formel, hvor vægten Wt,d af udtrykket t i dokumentet d gives ved: Wt,d = TFt,d log (N/DFt)
Afsluttende tanker
HulkApps har alt-i-en TF-IDF-rapportservices til Shopify, der hjælper butiksejere, ligesom dig, med at udtrække de mest beskrivende udtryk i et dokument / en hjemmeside...
Hvornår skal man bruge TF-IDF-analyse?
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