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:
Hvornår skal man bruge TF-IDF-analyse?
Hvorfor bruge TF-IDF-rapporten?
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...
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