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Marc Kupietzc6a66ee2023-10-23 13:18:48 +02001#' Get syntagmatic neighbours
Marc Kupietzbb4f54c2023-10-19 21:22:44 +02002#'
Marc Kupietzc6a66ee2023-10-23 13:18:48 +02003#' Get the syntagmatic neighbour predictions of a word from the DeReKoVecs model (see Fankhauser/Kupietz 2022, 2017).
4#'
Marc Kupietzbb4f54c2023-10-19 21:22:44 +02005#' @param word The word to get the syntagmatic neighbours for.
6#' @param ... Additional parameters to pass to the API.
7#'
Marc Kupietzc6a66ee2023-10-23 13:18:48 +02008#' @return Data frame with the syntagmatic neighbours of a node predicted from derekovecs model, with the following columns:
9#'
10#' \describe{
11#' \item{average}{⟨a⟩ - Average raw activation of the collocator in the columns selected by auto-focus.}
12#' \item{heat}{Vector of activation of the respective collocator in the slots around the target normalized by its maximum.}
13#' \item{max}{max(a) - Maximum activation of the collocator anywhere in the output layer.}
14#' \item{overall}{Σa/Σw – Sum of the activations over the whole window normalized by the total window sum (no auto-focus).}
15#' \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}
16#' \item{rank}{Frequency rank of predicted collocate}
17#' \item{word}{Predicted collocate}
18#' }
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020019#' @export
Marc Kupietze981eae2023-10-18 09:00:17 +020020syntagmaticNeighbours <- function(word = "Test", ...) {
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020021 derekovecsApiCall("", word = word, json = 1, ...)$collocators
Marc Kupietze981eae2023-10-18 09:00:17 +020022}
23
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020024#' Get count-based collocates
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020025#'
26#' Get the collocates of a word in the count-based dereko model.
27#'
28#' @param w The word to get the collocates for.
29#' @param ... Additional parameters to pass to the API.
30#'
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020031#' @return A data frame with the most salient collocates and their association scores.
32#' @seealso [collocationScores()] for details
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020033#' @export
Marc Kupietze981eae2023-10-18 09:00:17 +020034countbasedCollocates <- function(w = "Test", ...) {
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020035 derekovecsApiCall(method = "/getClassicCollocators", w = w, ...)$collocates
Marc Kupietze981eae2023-10-18 09:00:17 +020036}
37
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020038#' Get paradigmatic neighbours
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020039#'
40#' Get the paradigmatic neighbours of a word in the derekovecs model.
41#'
42#' @param word The word to get the paradigmatic neighbours for.
43#' @param ... Additional parameters to pass to the API.
44#' @return A list of words with their similarity scores.
45#' @export
46#'
Marc Kupietze981eae2023-10-18 09:00:17 +020047paradigmaticNeighbours <- function(word = "Test", ...) {
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020048 derekovecsApiCall("", word = word, json = 1, ...)$list[[1]]
Marc Kupietze981eae2023-10-18 09:00:17 +020049}
50
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020051#' Get collocation scores
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020052#'
53#' Calculate the association scores between a node (target word) and words in a window around the it.
54#'
55#' @param w The target word/node.
56#' @param c The collocate.
57#' @param ... Additional parameters to pass to the API.
58#'
59#' @return A one row data frame with collocate and its association scores.
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020060#' \describe{
61#' \item{word}{collocate}
62#' \item{f2}{abs. frequency of collocate}
63#' \item{f}{abs. frequency of collocation}
64#' \item{npmi}{normalized pmi (Bouma 2009)}
65#' \item{pmi}{pointwise mutual information}
66#' \item{dice}{dice score}
67#' \item{ld}{log-dice score (Rychlý 2008) for whole window}
68#' \item{lfmd}{log-frequency biased mutual dependency ≙ pmi³ (Dalle 1994; Thanopoulos et al. 2002)}
69#' \item{llr}{log-likelihood (Dunning 1993; Evert 2004)}
70#' \item{ln_count}{frequency of collocate as left neighbour of node}
71#' \item{ln_pmi}{pmi as left neighbour}
72#' \item{md}{mutual dependency ≙ pmi² (Dalle 1994; Thanopoulos et al. 2002)}
73#' \item{rn_count}{frequency of collocate as right neighbour of node}
74#' \item{rn_pmi}{pmi as right neighbour}
75#' \item{ldaf}{log-dice score for auto focus window}
76#' \item{win}{binary encoded positions at which the collocate appears at least once, e.g.: 1023 = 2^10-1 ≙ 11111 node 11111}
77#' \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)}
78#' }
79#' @references
80#' Daille, B. (1994): Approche mixte pour l’extraction automatique de terminologie: statistiques lexicales et filtres linguistiques. PhD thesis, Université Paris 7.
81#'
82#' Dunning, T. (1993): Accurate methods for the statistics of surprise and coincidence. Comput. Linguist. 19, 1 (March 1993), 61-74.
83#'
84#' 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.
85#' Free PDF available from <https://purl.org/stefan.evert/PUB/Evert2004phd.pdf>
86#'
87#' Thanopoulos, A., Fakotakis, N., Kokkinakis, G. (2002): Comparative evaluation of collocation extraction metrics. In: Proc. of LREC 2002: 620–625.
88#'
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020089#' @export
90#'
Marc Kupietze981eae2023-10-18 09:00:17 +020091collocationScores <- function(w, c, ...) {
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020092 derekovecsApiCall("/getCollocationAssociation",
93 w = w, c = c, ...)$collocates
Marc Kupietze981eae2023-10-18 09:00:17 +020094}
95
Marc Kupietzc6a66ee2023-10-23 13:18:48 +020096#' Get cosine similarity
Marc Kupietzbb4f54c2023-10-19 21:22:44 +020097#'
98#' @param w1 The first word.
99#' @param w2 The second word.
100#' @param ... Additional parameters to pass to the API.
101#'
102#' @return The cosine similarity between the two words.
103#' @export
104#'
105#' @description Calculate the cosine similarity between two words in the derekovecs model.
Marc Kupietze981eae2023-10-18 09:00:17 +0200106cosineSimilarity <- function(w1, w2, ...) {
Marc Kupietzbb4f54c2023-10-19 21:22:44 +0200107 derekovecsApiCall("/getSimilarity", w1 = w1, w2 = w2, ...)
108}
109
Marc Kupietzc6a66ee2023-10-23 13:18:48 +0200110#' Get the DeReKoVecs server
Marc Kupietzbb4f54c2023-10-19 21:22:44 +0200111#'
112#' @return The URL of the DeReKoVecs API server.
113#' @export
114#'
115derekovecsServer <- function() {
116 api_server <- Sys.getenv("DEREKOVECS_SERVER")
117 if (!identical(api_server, "")) {
118 return(api_server)
119 }
120 'https://corpora.ids-mannheim.de/openlab/derekovecs/'
121}
122
123#' DeReKoVecsCall
124#'
125#' Call the DeReKoVecs API.
126#'
127#' @param method The method to call.
128#' @param ... The parameters to pass to the method.
129#' @return The result of the call.
130#' @importFrom httr2 request req_url_path_append req_url_query req_perform resp_body_json
131#'
132#' @include utils-pipe.R
133#'
134derekovecsApiCall <- function(method = "", ...) {
135 httr2::request(derekovecsServer()) %>%
136 httr2::req_url_path_append(method) %>%
137 httr2::req_url_query(...) %>%
138 httr2::req_perform() %>%
139 httr2::resp_body_json(simplifyVector = TRUE)
Marc Kupietze981eae2023-10-18 09:00:17 +0200140}