textaKeyPhrases function

Returns the key talking points in sentences or documents.

This function returns the the key talking points in a list of sentences or documents. The following languages are currently supported: English, German, Spanish and Japanese.

Internally, this function invokes the Microsoft Cognitive Services Text Analytics REST API documented at https://www.microsoft.com/cognitive-services/en-us/text-analytics/documentation.

You MUST have a valid Microsoft Cognitive Services account and an API key for this function to work properly. See https://www.microsoft.com/cognitive-services/en-us/pricing

for details.

textaKeyPhrases(documents, languages = rep("en", length(documents)))

Arguments

• documents: (character vector) Vector of sentences or documents for which to extract key talking points.
• languages: (character vector) Languages of the sentences or documents, supported values: "en"(English, default), "de"(German), "es"(Spanish), "fr"(French), "ja"(Japanese)

Returns

An S3 object of the class texta. The results are stored in the results dataframe inside this object. The dataframe contains the original sentences or documents and their key talking points. If an error occurred during processing, the dataframe will also have an error

column that describes the error.

Examples

## Not run:

 docsText <- c(
   "Loved the food, service and atmosphere! We'll definitely be back.",
   "Very good food, reasonable prices, excellent service.",
   "It was a great restaurant.",
   "If steak is what you want, this is the place.",
   "The atmosphere is pretty bad but the food is quite good.",
   "The food is quite good but the atmosphere is pretty bad.",
   "I'm not sure I would come back to this restaurant.",
   "The food wasn't very good.",
   "While the food was good the service was a disappointment.",
   "I was very disappointed with both the service and my entree."
 )
 docsLanguage <- rep("en", length(docsText))

 tryCatch({

   # Get key talking points in documents
   docsKeyPhrases <- textaKeyPhrases(
     documents = docsText,    # Input sentences or documents
     languages = docsLanguage
     # "en"(English, default)|"de"(German)|"es"(Spanish)|"fr"(French)|"ja"(Japanese)
   )

   # Class and structure of docsKeyPhrases
   class(docsKeyPhrases)
   #> [1] "texta"
   str(docsKeyPhrases, max.level = 1)
   #> List of 3
   #>  $ results:'data.frame': 10 obs. of  2 variables:
   #>  $ json   : chr "{\"documents\":[{\"keyPhrases\":[\"atmosphere\",\"food\", __truncated__ ]}]}
   #>  $ request:List of 7
   #>   ..- attr(*, "class")= chr "request"
   #>  - attr(*, "class")= chr "texta"

   # Print results
   docsKeyPhrases
   #> texta [https://westus.api.cognitive.microsoft.com/text/analytics/v2.0/keyPhrases]
   #>
   #> -----------------------------------------------------------
   #>              text                       keyPhrases
   #> ------------------------------ ----------------------------
   #>  Loved the food, service and    atmosphere, food, service
   #>  atmosphere! We'll definitely
   #>            be back.
   #>
   #>   Very good food, reasonable   reasonable prices, good food
   #>   prices, excellent service.
   #>
   #>   It was a great restaurant.         great restaurant
   #>
   #>   If steak is what you want,           steak, place
   #>       this is the place.
   #>
   #>  The atmosphere is pretty bad        atmosphere, food
   #>  but the food is quite good.
   #>
   #>  The food is quite good but the       food, atmosphere
   #>   atmosphere is pretty bad.
   #>
   #> I'm not sure I would come back          restaurant
   #>      to this restaurant.
   #>
   #>   The food wasn't very good.               food
   #>
   #>  While the food was good the          service, food
   #> service was a disappointment.
   #>
   #>  I was very disappointed with        service, entree
   #>    both the service and my
   #>            entree.
   #> -----------------------------------------------------------

 }, error = function(err) {

   # Print error
   geterrmessage()

 })
## End(Not run)

Author(s)

Phil Ferriere pferriere@hotmail.com