You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
68 lines
4.6 KiB
68 lines
4.6 KiB
#' Get ids of duplicate documents that have a cosine similarity score higher than [threshold]
|
|
#'
|
|
#' Get ids of duplicate documents that have a cosine similarity score higher than [threshold]
|
|
#' @param row Row of grid to parse
|
|
#' @param grid A cross-table of all possible combinations of doctypes and dates
|
|
#' @param cutoff_lower Cutoff value for minimum cosine similarity above which documents are considered duplicates (inclusive)
|
|
#' @param cutoff_upper Cutoff value for maximum cosine similarity, above which documents are not considered duplicates (for debugging and manual parameter tuning, inclusive)
|
|
#' @param es_pwd Password for Elasticsearch read access
|
|
#' @param es_super Password for write access to ElasticSearch
|
|
#' @param words Document cutoff point in number of words. Documents are cut off at the last [.?!] before the cutoff (so document will be a little shorter than [words])
|
|
#' @param localhost Defaults to true. When true, connect to a local Elasticsearch instance on the default port (9200)
|
|
#' @param ver Short string (preferably a single word/sequence) indicating the version of the updated document (i.e. for a udpipe update this string might be 'udV2')
|
|
#' @return dupe_objects.json and data frame containing each id and all its duplicates. remove_ids.txt and character vector with list of ids to be removed. Files are in current working directory
|
|
#' @export
|
|
#' @examples
|
|
#' dupe_detect(1,grid,cutoff_lower, cutoff_upper = 1, es_pwd, es_super, words, localhost = T)
|
|
|
|
#################################################################################################
|
|
#################################### Duplicate detector ################################
|
|
#################################################################################################
|
|
dupe_detect <- function(row, grid, cutoff_lower, cutoff_upper = 1, es_pwd, es_super, words, localhost = T, ver) {
|
|
params <- grid[row,]
|
|
print(paste0('Parsing ',params$doctypes,' on ',params$dates ))
|
|
query <- paste0('doctype:\\"',params$doctypes,'\\" && publication_date:',params$dates,' && !computerCodes._delete:1')
|
|
out <- elasticizer(query_string(query, fields = c('country','text','title','subtitle','teaser','preteaser')), es_pwd = es_pwd, localhost= localhost)
|
|
if (class(out$hits$hits) != 'list') {
|
|
dfm <- dfm_gen(out, text = "full", words = words, clean = T)
|
|
if (sum(dfm[1,]) > 0) {
|
|
simil <- as.matrix(textstat_simil(dfm, margin="documents", method="cosine"))
|
|
diag(simil) <- NA
|
|
duplicates <- which(simil >= cutoff_lower & simil <= cutoff_upper, arr.ind = TRUE)
|
|
duplicates <- cbind(duplicates, rowid= rownames(duplicates))
|
|
if (length(duplicates) > 0) {
|
|
rownames(duplicates) <- seq(1:length(rownames(duplicates)))
|
|
df <- as.data.frame(duplicates, make.names = NA, stringsAsFactors = F) %>%
|
|
# bind_cols(colid = colnames(simil)[.['col']]) %>%
|
|
mutate(colid = colnames(simil)[as.numeric(col)]) %>%
|
|
.[,c(3,4)] %>%
|
|
group_by(colid) %>% summarise(rowid=list(rowid))
|
|
text <- capture.output(stream_out(df))
|
|
# write(text[-length(text)], file = paste0(getwd(),'/dupe_objects.json'), append=T)
|
|
simil[upper.tri(simil)] <- NA
|
|
# write(unique(rownames(which(simil >= cutoff_lower & simil <= cutoff_upper, arr.ind = TRUE))),
|
|
# file = paste0(getwd(),'/remove_ids.txt'),
|
|
# append=T)
|
|
dupe_delete <- data.frame(id=unique(rownames(which(simil >= cutoff_lower & simil <= cutoff_upper, arr.ind = TRUE))),
|
|
dupe_delete = rep(1,length(unique(rownames(which(simil >= cutoff_lower & simil <= cutoff_upper, arr.ind = TRUE))))))
|
|
bulk <- c(apply(df, 1, bulk_writer, varname='duplicates', type = 'set', ver = ver),
|
|
apply(dupe_delete, 1, bulk_writer, varname='_delete', type = 'set', ver = ver))
|
|
res <- elastic_update(bulk, es_super = es_super, localhost = localhost)
|
|
return(paste0('Checked ',params$doctypes,' on ',params$dates ))
|
|
} else {
|
|
return(paste0('No duplicates for ',params$doctypes,' on ',params$dates ))
|
|
}
|
|
} else {
|
|
return(paste0('No results for ',params$doctypes,' on ',params$dates ))
|
|
}
|
|
} else {
|
|
return(paste0('No results for ',params$doctypes,' on ',params$dates ))
|
|
}
|
|
### Dummy code to verify that filtering out unique ids using the bottom half of the matrix actually works
|
|
# id_filter <- unique(rownames(which(simil >= cutoff, arr.ind = TRUE)))
|
|
# dfm_nodupes <- dfm_subset(dfm, !(docnames(dfm) %in% id_filter))
|
|
# simil_nodupes <- as.matrix(textstat_simil(dfm_nodupes, margin="documents", method="cosine"))
|
|
# diag(simil_nodupes) <- NA
|
|
# which(simil_nodupes >= cutoff, arr.ind = TRUE)
|
|
}
|