Calculate Similarity Robust

Calculates document similarity with fallback methods and diagnostics. Attempts embeddings first, falls back to Jaccard similarity if needed.

Usage

calculate_similarity_robust(
  texts,
  method = "embeddings",
  embedding_model = "all-MiniLM-L6-v2",
  cache_embeddings = TRUE,
  min_word_length = 3,
  doc_names = NULL
)

Arguments

texts

Character vector of texts

method

Similarity method ("embeddings" or "jaccard")

embedding_model

Model name for embeddings (default: "all-MiniLM-L6-v2")

cache_embeddings

Logical, cache embeddings (default: TRUE)

min_word_length

Minimum word length for Jaccard (default: 3)

doc_names

Optional document names

Value

List containing similarity matrix, method used, embeddings, and diagnostics

Examples

if (FALSE) { # \dontrun{
texts <- c(
  "Assistive technology supports learning.",
  "Technology helps students with disabilities.",
  "Machine learning improves accuracy."
)

result <- calculate_similarity_robust(texts)
print(result$similarity_matrix)
print(result$diagnostics)
} # }