textaDetectTopicsStatus function

Retrieves the status of a topic detection operation submitted for processing.

This function retrieves the status of an asynchronous topic detection operation previously submitted for processing. If the operation has reached a 'Succeeded' state, this function will also return the results.

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.

textaDetectTopicsStatus(operation, verbose = FALSE)

Arguments

• operation: (textatopics) textatopics S3 object returned by the original call to textaDetectTopics.
• verbose: (logical) If set to TRUE, print poll status to stdout.

Returns

An S3 object of the class textatopics with the results of the topic detection operation. See textatopics for details.

Examples

## Not run:

 load("./data/yelpChineseRestaurantReviews.rda")
 set.seed(1234)
 documents <- sample(yelpChReviews$text, 1000)

 tryCatch({

   # Start async topic detection
   operation <- textaDetectTopics(
     documents,                  # At least 100 docs/sentences
     stopWords = NULL,           # Stop word list (optional)
     topicsToExclude = NULL,     # Topics to exclude (optional)
     minDocumentsPerWord = NULL, # Threshold to exclude rare topics (optional)
     maxDocumentsPerWord = NULL, # Threshold to exclude ubiquitous topics (optional)
     resultsPollInterval = 0L    # Poll interval (in s, default: 30s, use 0L for async)
   )

   # Poll the servers until the work completes or until we time out
   resultsPollInterval <- 60L
   resultsTimeout <- 1200L
   startTime <- Sys.time()
   endTime <- startTime + resultsTimeout

   while (Sys.time() <= endTime) {
     sleepTime <- startTime + resultsPollInterval - Sys.time()
     if (sleepTime > 0)
       Sys.sleep(sleepTime)
     startTime <- Sys.time()

     # Poll for results
     topics <- textaDetectTopicsStatus(operation)
     if (topics$status != "NotStarted" && topics$status != "Running")
       break;
   }

   # Class and structure of topics
   class(topics)
   #> [1] "textatopics"

   str(topics, max.level = 1)
   #> List of 8
   #> $ status          : chr "Succeeded"
   #> $ operationId     : chr "30334a3e1e28406a80566bb76ff04884"
   #> $ operationType   : chr "topics"
   #> $ documents       :'data.frame':  1000 obs. of  2 variables:
   #> $ topics          :'data.frame':  71 obs. of  3 variables:
   #> $ topicAssignments:'data.frame':  502 obs. of  3 variables:
   #> $ json            : chr "{\"status\":\"Succeeded\",\"createdDateTime\": __truncated__ }
   #> $ request         :List of 7
   #> ..- attr(*, "class")= chr "request"
   #> - attr(*, "class")= chr "textatopics"

   # Print results
   topics
   #> textatopics [https://westus.api.cognitive.microsoft.com/text/analytics/ __truncated__ ]
   #> status: Succeeded
   #> operationId: 30334a3e1e28406a80566bb76ff04884
   #> operationType: topics
   #> topics (first 20):
   #> ------------------------
   #>    keyPhrase      score
   #> ---------------- -------
   #>     portions       35
   #>   noodle soup      30
   #>    vegetables      20
   #>       tofu         19
   #>      garlic        17
   #>     Eggplant       15
   #>       Pad          15
   #>      combo         13
   #> Beef Noodle Soup   13
   #>      House         12
   #>      entree        12
   #>     wontons        12
   #>     Pei Wei        12
   #>  mongolian beef    11
   #>       crab         11
   #>      Panda         11
   #>       bean         10
   #>    dumplings        9
   #>     veggies         9
   #>      decor          9
   #> ------------------------

 }, error = function(err) {

   # Print error
   geterrmessage()

 })
## End(Not run)

Author(s)

Phil Ferriere pferriere@hotmail.com