Add documentation on the data frames returned
Change-Id: Ifdc9b27829c6ab01aa4d6d7b88c339884a470877
diff --git a/R/derekovecs.R b/R/derekovecs.R
index 2b0d492..53efb67 100644
--- a/R/derekovecs.R
+++ b/R/derekovecs.R
@@ -1,29 +1,41 @@
-#' syntagmaticNeighbours
+#' Get syntagmatic neighbours
#'
-#' Get the syntagmatic neighbours of a word from the predictive derekovecs model.
+#' Get the syntagmatic neighbour predictions of a word from the DeReKoVecs model (see Fankhauser/Kupietz 2022, 2017).
+#'
#' @param word The word to get the syntagmatic neighbours for.
#' @param ... Additional parameters to pass to the API.
#'
-#' @return Data frame syntagmatic neighbours of a word from the predictive derekovecs model.
+#' @return Data frame with the syntagmatic neighbours of a node predicted from derekovecs model, with the following columns:
+#'
+#' \describe{
+#' \item{average}{⟨a⟩ - Average raw activation of the collocator in the columns selected by auto-focus.}
+#' \item{heat}{Vector of activation of the respective collocator in the slots around the target normalized by its maximum.}
+#' \item{max}{max(a) - Maximum activation of the collocator anywhere in the output layer.}
+#' \item{overall}{Σa/Σw – Sum of the activations over the whole window normalized by the total window sum (no auto-focus).}
+#' \item{pos}{Binary encoded position of where in the window around the node the collocate is predecited with above 0 probability, e.g. 64 = 2^6 ≙ 00010 node 00000}
+#' \item{rank}{Frequency rank of predicted collocate}
+#' \item{word}{Predicted collocate}
+#' }
#' @export
syntagmaticNeighbours <- function(word = "Test", ...) {
derekovecsApiCall("", word = word, json = 1, ...)$collocators
}
-#' countbasedCollocates
+#' Get count-based collocates
#'
#' Get the collocates of a word in the count-based dereko model.
#'
#' @param w The word to get the collocates for.
#' @param ... Additional parameters to pass to the API.
#'
-#' @return A data fram with the most salient collcates and their association scores.
+#' @return A data frame with the most salient collocates and their association scores.
+#' @seealso [collocationScores()] for details
#' @export
countbasedCollocates <- function(w = "Test", ...) {
derekovecsApiCall(method = "/getClassicCollocators", w = w, ...)$collocates
}
-#' paradigmaticNeighbours
+#' Get paradigmatic neighbours
#'
#' Get the paradigmatic neighbours of a word in the derekovecs model.
#'
@@ -36,7 +48,7 @@
derekovecsApiCall("", word = word, json = 1, ...)$list[[1]]
}
-#' collocationScores
+#' Get collocation scores
#'
#' Calculate the association scores between a node (target word) and words in a window around the it.
#'
@@ -45,6 +57,35 @@
#' @param ... Additional parameters to pass to the API.
#'
#' @return A one row data frame with collocate and its association scores.
+#' \describe{
+#' \item{word}{collocate}
+#' \item{f2}{abs. frequency of collocate}
+#' \item{f}{abs. frequency of collocation}
+#' \item{npmi}{normalized pmi (Bouma 2009)}
+#' \item{pmi}{pointwise mutual information}
+#' \item{dice}{dice score}
+#' \item{ld}{log-dice score (Rychlý 2008) for whole window}
+#' \item{lfmd}{log-frequency biased mutual dependency ≙ pmi³ (Dalle 1994; Thanopoulos et al. 2002)}
+#' \item{llr}{log-likelihood (Dunning 1993; Evert 2004)}
+#' \item{ln_count}{frequency of collocate as left neighbour of node}
+#' \item{ln_pmi}{pmi as left neighbour}
+#' \item{md}{mutual dependency ≙ pmi² (Dalle 1994; Thanopoulos et al. 2002)}
+#' \item{rn_count}{frequency of collocate as right neighbour of node}
+#' \item{rn_pmi}{pmi as right neighbour}
+#' \item{ldaf}{log-dice score for auto focus window}
+#' \item{win}{binary encoded positions at which the collocate appears at least once, e.g.: 1023 = 2^10-1 ≙ 11111 node 11111}
+#' \item{afwin}{binary encoded auto-focus window (see Perkuhn et al. 2012: E8-15), e.g. 64 = 2^6 ≙ 00010 node 00000 (Aus gutem Grund)}
+#' }
+#' @references
+#' Daille, B. (1994): Approche mixte pour l’extraction automatique de terminologie: statistiques lexicales et filtres linguistiques. PhD thesis, Université Paris 7.
+#'
+#' Dunning, T. (1993): Accurate methods for the statistics of surprise and coincidence. Comput. Linguist. 19, 1 (March 1993), 61-74.
+#'
+#' Evert, Stefan (2004): The Statistics of Word Cooccurrences: Word Pairs and Collocations. PhD dissertation, IMS, University of Stuttgart. Published in 2005, URN urn:nbn:de:bsz:93-opus-23714.
+#' Free PDF available from <https://purl.org/stefan.evert/PUB/Evert2004phd.pdf>
+#'
+#' Thanopoulos, A., Fakotakis, N., Kokkinakis, G. (2002): Comparative evaluation of collocation extraction metrics. In: Proc. of LREC 2002: 620–625.
+#'
#' @export
#'
collocationScores <- function(w, c, ...) {
@@ -52,7 +93,7 @@
w = w, c = c, ...)$collocates
}
-#' cosineSimilarity
+#' Get cosine similarity
#'
#' @param w1 The first word.
#' @param w2 The second word.
@@ -66,7 +107,7 @@
derekovecsApiCall("/getSimilarity", w1 = w1, w2 = w2, ...)
}
-#' DeReKoVecsServer
+#' Get the DeReKoVecs server
#'
#' @return The URL of the DeReKoVecs API server.
#' @export