This function calculates the topic similarity between two conversations using either
Latent Dirichlet Allocation (LDA) or Latent Semantic Analysis (LSA).
Usage
topic_similarity(conv1, conv2, method = "lda", num_topics = 2)
Arguments
- conv1
A character vector representing the first conversation
- conv2
A character vector representing the second conversation
- method
A character string specifying the method to use: "lda" or "lsa"
- num_topics
An integer specifying the number of topics to use in the model
Value
A numeric value representing the topic similarity
Examples
conv1 <- c("I love pizza", "Pizza is my favorite food")
conv2 <- c("I prefer pasta", "Pasta is delicious")
topic_similarity(conv1, conv2, method = "lda", num_topics = 2)
#> [1] 0.9995592
topic_similarity(conv1, conv2, method = "lsa", num_topics = 2)
#> [,1]
#> [1,] 1