Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 1 | setGeneric("collocationAnalysis", function(kco, ...) standardGeneric("collocationAnalysis") ) |
| 2 | |
| 3 | #' Collocation analysis |
| 4 | #' |
| 5 | #' @aliases collocationAnalysis |
| 6 | #' |
| 7 | #' @description |
Marc Kupietz | 67edcb5 | 2021-09-20 21:54:24 +0200 | [diff] [blame] | 8 | #' `r lifecycle::badge("experimental")` |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 9 | #' |
| 10 | #' Performs a collocation analysis for the given node (or query) |
| 11 | #' in the given virtual corpus. |
| 12 | #' |
| 13 | #' @details |
| 14 | #' The collocation analysis is currently implemented on the client side, as some of the |
| 15 | #' functionality is not yet provided by the KorAP backend. Mainly for this reason |
| 16 | #' it is very slow (several minutes, up to hours), but on the other hand very flexible. |
| 17 | #' You can, for example, perform the analysis in arbitrary virtual corpora, use complex node queries, |
| 18 | #' and look for expression-internal collocates using the focus function (see examples and demo). |
| 19 | #' |
| 20 | #' To increase speed at the cost of accuracy and possible false negatives, |
| 21 | #' you can decrease searchHitsSampleLimit and/or topCollocatesLimit and/or set exactFrequencies to FALSE. |
| 22 | #' |
| 23 | #' Note that currently not the tokenization provided by the backend, i.e. the corpus itself, is used, but a tinkered one. |
| 24 | #' This can also lead to false negatives and to frequencies that differ from corresponding ones acquired via the web |
| 25 | #' user interface. |
| 26 | #' |
| 27 | #' @family collocation analysis functions |
| 28 | #' |
Marc Kupietz | 67edcb5 | 2021-09-20 21:54:24 +0200 | [diff] [blame] | 29 | #' @param lemmatizeNodeQuery if TRUE, node query will be lemmatized, i.e. `x -> [tt/l=x]` |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 30 | #' @param minOccur minimum absolute number of observed co-occurrences to consider a collocate candidate |
| 31 | #' @param topCollocatesLimit limit analysis to the n most frequent collocates in the search hits sample |
| 32 | #' @param searchHitsSampleLimit limit the size of the search hits sample |
| 33 | #' @param stopwords vector of stopwords not to be considered as collocates |
| 34 | #' @param exactFrequencies if FALSE, extrapolate observed co-occurrence frequencies from frequencies in search hits sample, otherwise retrieve exact co-occurrence frequencies |
| 35 | #' @param seed seed for random page collecting order |
Marc Kupietz | 67edcb5 | 2021-09-20 21:54:24 +0200 | [diff] [blame] | 36 | #' @param expand if TRUE, `node` and `vc` parameters are expanded to all of their combinations |
| 37 | #' @param ... more arguments will be passed to [collocationScoreQuery()] |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 38 | #' @inheritParams collocationScoreQuery,KorAPConnection-method |
| 39 | #' @return Tibble with top collocates, association scores, corresponding URLs for web user interface queries, etc. |
| 40 | #' |
| 41 | #' @importFrom stringr str_match str_split str_detect |
| 42 | #' @importFrom dplyr anti_join arrange desc slice_head bind_rows |
| 43 | #' @importFrom purrr pmap |
| 44 | #' @importFrom tidyr expand_grid |
| 45 | #' |
| 46 | #' @examples |
Marc Kupietz | 6ae7605 | 2021-09-21 10:34:00 +0200 | [diff] [blame] | 47 | #' \dontrun{ |
| 48 | #' |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 49 | #' # Find top collocates of "Packung" inside and outside the sports domain. |
| 50 | #' new("KorAPConnection", verbose = TRUE) %>% |
| 51 | #' collocationAnalysis("Packung", vc=c("textClass=sport", "textClass!=sport"), |
| 52 | #' leftContextSize=1, rightContextSize=1, topCollocatesLimit=20) %>% |
| 53 | #' dplyr::filter(logDice >= 5) |
| 54 | #' } |
| 55 | #' |
Marc Kupietz | 6ae7605 | 2021-09-21 10:34:00 +0200 | [diff] [blame] | 56 | #' \dontrun{ |
| 57 | #' |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 58 | #' # Identify the most prominent light verb construction with "in ... setzen". |
| 59 | #' # Note that, currently, the use of focus function disallows exactFrequencies. |
| 60 | #' new("KorAPConnection", verbose = TRUE) %>% |
| 61 | #' collocationAnalysis("focus(in [tt/p=NN] {[tt/l=setzen]})", |
| 62 | #' leftContextSize=1, rightContextSize=0, exactFrequencies=FALSE, topCollocatesLimit=20) |
| 63 | #' } |
| 64 | #' |
| 65 | #' @export |
| 66 | setMethod("collocationAnalysis", "KorAPConnection", |
| 67 | function(kco, |
| 68 | node, |
| 69 | vc = "", |
| 70 | lemmatizeNodeQuery = FALSE, |
| 71 | minOccur = 5, |
| 72 | leftContextSize = 5, |
| 73 | rightContextSize = 5, |
| 74 | topCollocatesLimit = 200, |
| 75 | searchHitsSampleLimit = 20000, |
| 76 | ignoreCollocateCase = FALSE, |
| 77 | withinSpan = ifelse(exactFrequencies, "base/s=s", ""), |
| 78 | exactFrequencies = TRUE, |
| 79 | stopwords = RKorAPClient::synsemanticStopwords(), |
| 80 | seed = 7, |
| 81 | expand = length(vc) != length(node), |
| 82 | ...) { |
| 83 | # https://stackoverflow.com/questions/8096313/no-visible-binding-for-global-variable-note-in-r-cmd-check |
| 84 | word <- frequency <- NULL |
| 85 | |
| 86 | if(!exactFrequencies && (!is.na(withinSpan) && !is.null(withinSpan) && nchar(withinSpan)>0 )) { |
| 87 | stop(sprintf("Not empty withinSpan (='%s') requires exactFrequencies=TRUE", withinSpan), call. = FALSE) |
| 88 | } |
| 89 | |
Marc Kupietz | 581a29b | 2021-09-04 20:51:04 +0200 | [diff] [blame] | 90 | warnIfNoAccessToken(kco) |
| 91 | |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 92 | if (lemmatizeNodeQuery) { |
| 93 | node <- lemmatizeWordQuery(node) |
| 94 | } |
| 95 | |
| 96 | if (length(node) > 1 || length(vc) > 1) { |
| 97 | grid <- if (expand) expand_grid(node=node, vc=vc) else tibble(node=node, vc=vc) |
| 98 | purrr::pmap(grid, function(node, vc, ...) |
| 99 | collocationAnalysis(kco, |
| 100 | node =node, |
| 101 | vc = vc, |
| 102 | minOccur = minOccur, |
| 103 | leftContextSize = leftContextSize, |
| 104 | rightContextSize = rightContextSize, |
| 105 | topCollocatesLimit = topCollocatesLimit, |
| 106 | searchHitsSampleLimit = searchHitsSampleLimit, |
| 107 | ignoreCollocateCase = ignoreCollocateCase, |
| 108 | withinSpan = withinSpan, |
| 109 | exactFrequencies = exactFrequencies, |
| 110 | stopwords = stopwords, |
| 111 | seed = seed, |
| 112 | expand = expand, |
| 113 | ...) ) %>% |
| 114 | bind_rows() |
| 115 | } else { |
| 116 | set.seed(seed) |
| 117 | candidates <- collocatesQuery( |
| 118 | kco, |
| 119 | node, |
| 120 | vc = vc, |
| 121 | minOccur = minOccur, |
| 122 | leftContextSize = leftContextSize, |
| 123 | rightContextSize = rightContextSize, |
| 124 | searchHitsSampleLimit = searchHitsSampleLimit, |
| 125 | ignoreCollocateCase = ignoreCollocateCase, |
| 126 | stopwords = stopwords, |
| 127 | ... |
| 128 | ) |
| 129 | |
| 130 | if (nrow(candidates) > 0) { |
| 131 | candidates <- candidates %>% |
| 132 | filter(frequency >= minOccur) %>% |
| 133 | head(topCollocatesLimit) |
| 134 | collocationScoreQuery( |
| 135 | kco, |
| 136 | node = node, |
| 137 | collocate = candidates$word, |
| 138 | vc = vc, |
| 139 | leftContextSize = leftContextSize, |
| 140 | rightContextSize = rightContextSize, |
| 141 | observed = if (exactFrequencies) NA else candidates$frequency, |
| 142 | ignoreCollocateCase = ignoreCollocateCase, |
| 143 | withinSpan = withinSpan, |
| 144 | ... |
| 145 | ) %>% |
| 146 | filter(.$O >= minOccur) %>% |
| 147 | dplyr::arrange(dplyr::desc(logDice)) |
| 148 | } else { |
| 149 | tibble() |
| 150 | } |
| 151 | } |
| 152 | } |
| 153 | ) |
| 154 | |
| 155 | #' @importFrom magrittr debug_pipe |
| 156 | #' @importFrom stringr str_match str_split str_detect |
| 157 | #' @importFrom dplyr as_tibble tibble rename filter anti_join tibble bind_rows case_when |
| 158 | #' |
| 159 | snippet2FreqTable <- function(snippet, |
| 160 | minOccur = 5, |
| 161 | leftContextSize = 5, |
| 162 | rightContextSize = 5, |
| 163 | ignoreCollocateCase = FALSE, |
| 164 | stopwords = c(), |
| 165 | tokenizeRegex = "([! )(\uc2\uab,.:?\u201e\u201c\'\"]+|")", |
| 166 | oldTable = data.frame(word = rep(NA, 1), frequency = rep(NA, 1)), |
| 167 | verbose = TRUE) { |
| 168 | word <- NULL # https://stackoverflow.com/questions/8096313/no-visible-binding-for-global-variable-note-in-r-cmd-check |
| 169 | frequency <- NULL |
| 170 | |
| 171 | if (length(snippet) < 1) { |
| 172 | dplyr::tibble(word=c(), frequency=c()) |
| 173 | } else if (length(snippet) > 1) { |
Marc Kupietz | d07bf19 | 2021-09-04 20:24:44 +0200 | [diff] [blame] | 174 | log.info(verbose, paste("Joinging", length(snippet), "kwics\n")) |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 175 | for (s in snippet) { |
| 176 | oldTable <- snippet2FreqTable( |
| 177 | s, |
| 178 | leftContextSize = leftContextSize, |
| 179 | rightContextSize = rightContextSize, |
| 180 | oldTable = oldTable, |
| 181 | stopwords = stopwords |
| 182 | ) |
| 183 | } |
Marc Kupietz | d07bf19 | 2021-09-04 20:24:44 +0200 | [diff] [blame] | 184 | log.info(verbose, paste("Aggregating", length(oldTable$word), "tokens\n")) |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 185 | oldTable %>% |
| 186 | group_by(word) %>% |
| 187 | mutate(word = dplyr::case_when(ignoreCollocateCase ~ tolower(word), TRUE ~ word)) %>% |
| 188 | summarise(frequency=sum(frequency), .groups = "drop") %>% |
| 189 | arrange(desc(frequency)) |
| 190 | } else { |
| 191 | stopwordsTable <- dplyr::tibble(word=stopwords) |
| 192 | match <- |
| 193 | str_match( |
| 194 | snippet, |
| 195 | '<span class="context-left">(<span class="more"></span>)?(.*[^ ]) *</span><span class="match"><mark>.*</mark></span><span class="context-right"> *([^<]*)' |
| 196 | ) |
| 197 | |
| 198 | left <- if(leftContextSize > 0) |
| 199 | tail(unlist(str_split(match[1, 3], tokenizeRegex)), leftContextSize) |
| 200 | else |
| 201 | "" |
| 202 | # cat(paste("left:", left, "\n", collapse=" ")) |
| 203 | |
| 204 | right <- if(rightContextSize > 0) |
| 205 | head(unlist(str_split(match[1, 4], tokenizeRegex)), rightContextSize) |
| 206 | else |
| 207 | "" |
| 208 | # cat(paste("right:", right, "\n", collapse=" ")) |
| 209 | |
| 210 | if(is.na(left) || is.na(right) || length(left) + length(right) == 0) { |
| 211 | oldTable |
| 212 | } else { |
| 213 | table(c(left, right)) %>% |
| 214 | dplyr::as_tibble(.name_repair = "minimal") %>% |
| 215 | dplyr::rename(word = 1, frequency = 2) %>% |
| 216 | dplyr::filter(str_detect(word, '^[:alnum:]+-?[:alnum:]*$')) %>% |
| 217 | dplyr::anti_join(stopwordsTable, by="word") %>% |
| 218 | dplyr::bind_rows(oldTable) |
| 219 | } |
| 220 | } |
| 221 | } |
| 222 | |
| 223 | #' Preliminary synsemantic stopwords function |
| 224 | #' |
| 225 | #' @description |
Marc Kupietz | 67edcb5 | 2021-09-20 21:54:24 +0200 | [diff] [blame] | 226 | #' `r lifecycle::badge("experimental")` |
Marc Kupietz | dbd431a | 2021-08-29 12:17:45 +0200 | [diff] [blame] | 227 | #' |
| 228 | #' Preliminary synsemantic stopwords function to be used in collocation analysis. |
| 229 | #' |
| 230 | #' @details |
| 231 | #' Currently only suitable for German. See stopwords package for other languages. |
| 232 | #' |
| 233 | #' @param ... future arguments for language detection |
| 234 | #' |
| 235 | #' @family collocation analysis functions |
| 236 | #' @return Vector of synsemantic stopwords. |
| 237 | #' @export |
| 238 | synsemanticStopwords <- function(...) { |
| 239 | res <- c( |
| 240 | "der", |
| 241 | "die", |
| 242 | "und", |
| 243 | "in", |
| 244 | "den", |
| 245 | "von", |
| 246 | "mit", |
| 247 | "das", |
| 248 | "zu", |
| 249 | "im", |
| 250 | "ist", |
| 251 | "auf", |
| 252 | "sich", |
| 253 | "Die", |
| 254 | "des", |
| 255 | "dem", |
| 256 | "nicht", |
| 257 | "ein", |
| 258 | "eine", |
| 259 | "es", |
| 260 | "auch", |
| 261 | "an", |
| 262 | "als", |
| 263 | "am", |
| 264 | "aus", |
| 265 | "Der", |
| 266 | "bei", |
| 267 | "er", |
| 268 | "dass", |
| 269 | "sie", |
| 270 | "nach", |
| 271 | "um", |
| 272 | "Das", |
| 273 | "zum", |
| 274 | "noch", |
| 275 | "war", |
| 276 | "einen", |
| 277 | "einer", |
| 278 | "wie", |
| 279 | "einem", |
| 280 | "vor", |
| 281 | "bis", |
| 282 | "\u00fcber", |
| 283 | "so", |
| 284 | "aber", |
| 285 | "Eine", |
| 286 | "diese", |
| 287 | "Diese", |
| 288 | "oder" |
| 289 | ) |
| 290 | return(res) |
| 291 | } |
| 292 | |
| 293 | collocatesQuery <- |
| 294 | function(kco, |
| 295 | query, |
| 296 | vc = "", |
| 297 | minOccur = 5, |
| 298 | leftContextSize = 5, |
| 299 | rightContextSize = 5, |
| 300 | searchHitsSampleLimit = 20000, |
| 301 | ignoreCollocateCase = FALSE, |
| 302 | stopwords = c(), |
| 303 | ...) { |
| 304 | frequency <- NULL |
| 305 | q <- corpusQuery(kco, query, vc, metadataOnly = F, ...) |
| 306 | if(q@totalResults == 0) { |
| 307 | tibble(word=c(), frequency=c()) |
| 308 | } else { |
| 309 | q <- fetchNext(q, maxFetch=searchHitsSampleLimit, randomizePageOrder=TRUE) |
| 310 | snippet2FreqTable((q@collectedMatches)$snippet, |
| 311 | minOccur = minOccur, |
| 312 | leftContextSize = leftContextSize, |
| 313 | rightContextSize = rightContextSize, |
| 314 | ignoreCollocateCase = ignoreCollocateCase, |
| 315 | stopwords = stopwords, |
| 316 | verbose = kco@verbose) %>% |
| 317 | mutate(frequency = frequency * q@totalResults / min(q@totalResults, searchHitsSampleLimit)) %>% |
| 318 | filter(frequency >= minOccur) |
| 319 | } |
| 320 | } |