Abstract
This process matches the one-word linguistic skills from the EPAS CVs to the one-word skills from ESCO.# http://rmarkdown.rstudio.com/html_document_format.htm
sourceTimeNeeded <- c(0);
source.starting.time <- proc.time()[3]Information about the libraries, environment, sources used and their execution is reported. Aditional information is provided within section tabs. Navigating through the report is also possible through the table of contents. Tables reported, can be dynamically filtered, searched ordered and exported into various formats.
librariesVersion <- c()
for(i in 1:length(libraries))
librariesVersion <- c(librariesVersion, paste(packageVersion(libraries[i] )))
librariesLoaded <- lapply(libraries, require, character.only = TRUE) ## Loading required package: magrittr## Loading required package: DT## Loading required package: text2vec## Loading required package: stringdist##
## Attaching package: 'stringdist'## The following object is masked from 'package:magrittr':
##
## extract## Loading required package: parallel../000.core/00.01.libraries.R completed in 2.01 seconds
sourceTimeNeeded <- c( sourceTimeNeeded, timeNeeded)
source.starting.time <- proc.time()[3]
## Base functions
# ESCO skills
# @authors ds@eworx.gr
repository <- "/data/generic/"
getSourcePath <- function(filename, baseFolder = repository){
return(paste(baseFolder, filename, sep = ""))
}
readData <- function(filename, colClasses = c(), baseFolder = repository, header = TRUE, sep = "\t", encoding = "UTF-8", stringsAsFactors = TRUE, na.strings = c("", "NULL"), verbose = FALSE){
if(length(colClasses) == 0)
return (data.table::fread(input = getSourcePath(filename, baseFolder), header = header, sep = sep, encoding = encoding, stringsAsFactors = stringsAsFactors, verbose = verbose, showProgress = TRUE, na.strings = na.strings ) )
return (data.table::fread(input = getSourcePath(filename, baseFolder), colClasses = colClasses, header = header, sep = sep, encoding = encoding, verbose = verbose, showProgress = TRUE, na.strings = na.strings ) )
}
#rds for small disk space & fst for fast load
saveBinary <- function(data, filename = filename, baseFolder = repository, format = "rds"){
fileName <- getSourcePath(filename, baseFolder)
dir.create(dirname(fileName), recursive = TRUE, showWarnings = FALSE)
if(format == "rds") saveRDS(data, fileName)
if(format == "fst") fst::write_fst(data, fileName)
}
#alternative for rough read write operations
saveRDS_ <- function(object, file){
dir.create(dirname(file), recursive = TRUE, showWarnings = FALSE)
saveRDS(object, file)
}
#rds for small disk space & fst for fast load
loadBinary <- function(filename, baseFolder = repository, format = "rds", as.data.table = TRUE){
if(format == "rds"){return(readRDS(getSourcePath(filename, baseFolder)))}
if(format == "fst"){return(fst::read_fst(getSourcePath(filename, baseFolder), as.data.table = as.data.table))}
}
rowColumns <- function(data){
return(paste( format(nrow(data), big.mark=","), "Rows X ", ncol(data), "Columns"))
}
publishIncludeCss <- function(){
sourceFile <- "/data/jobs/wp41.analysis/000.core/include.css"
destinatinoFile <- "/data/tmpfs/results/include.css"
if (!file.exists(destinatinoFile)) {
return (file.copy(sourceFile, destinatinoFile))
}else{
return(TRUE);
}
}
#as the mountstorage is on memory make sure the asset include.css is there.
summariseTable <- function(data){
return(data.frame(unclass(summary(data)), check.names = FALSE, stringsAsFactors = FALSE))
#return(do.call(cbind, lapply(data, summary)))
}
factoriseCharacterColumns <- function(data){
for(name in names(data)){
if( class(data[[name]]) =="character"){
data[[name]] <- as.factor(data[[name]])
}
}
return(data)
}
############################
# https://rstudio.github.io/DT/010-style.html
#https://rpubs.com/marschmi/RMarkdown
capitalise <- function(x) paste0(toupper(substring(x, 1, 1)), substring(x, 2, nchar(x)))
styliseDTNumericalColumn <- function(data, result, columnName, color, columnsName_original ){
if(columnName%in% columnsName_original){
result <- result %>% formatStyle(
columnName,
background = styleColorBar(data[[columnName]], color),
backgroundSize = '100% 90%',
backgroundRepeat = 'no-repeat',
backgroundPosition = 'center'
)
}
return(result)
}
reportTabularData <- function(data, anonymize=TRUE){
if(anonymize)return()
columnsName <- names(data)
columnsName <- lapply(columnsName, capitalise)
columnsName_original <- names(data)
result <-
DT::datatable(
data,
class = 'cell-border stripe',
filter = 'top',
rownames = FALSE,
colnames = columnsName,
extensions = 'Buttons',
options = list(
pageLength = 20,
columnDefs = list(list(className = 'dt-left', targets = "_all")),
dom = 'Bfrtip',
buttons = c('copy', 'csv', 'excel', 'pdf'),
searchHighlight = TRUE,
initComplete = JS(
"function(settings, json) {",
"$(this.api().table().header()).css({'border': '1px solid'});",
"}"
)
)
)
result <- styliseDTNumericalColumn(data,result, "Count", 'steelblue', columnsName_original)
result <- styliseDTNumericalColumn(data,result, "sourceTimeNeeded", '#808080', columnsName_original)
result <- styliseDTNumericalColumn(data,result, "timeNeeded", '#808080', columnsName_original)
#result <- styliseDTNumericalColumn(data,result, "percentMatch", '#5fba7d', columnsName_original)
result <- styliseDTNumericalColumn(data,result, "percentMatch", '#4682b4', columnsName_original)
return(result)
}
fonts <- list(
sans = "DejaVu Serif",
mono = "DejaVu Serif",
`Times New Roman` = "DejaVu Serif"
)
#read_xml_to_list <- function(filepath, is.gz = FALSE){
# if(is.gz){
# temp_data <- paste0(repository, "data/delete.me")
# result <- xmlToList(xmlParse(gunzip(filepath, destname = temp_data, remove =FALSE)))
# Sys.chmod(file.path(temp_data), "777", use_umask = FALSE)
# unlink(temp_data)
# result
# }else{
# xmlToList(xmlParse(filepath))
# }
#}
#transpose_list_to_dt <- function(data_list){
# dt <- t(as.data.table(data_list))
# dt <- as.data.table(dt)
# dt[, (names(dt)) := lapply(.SD, unlist), .SDcols = 1:ncol(dt)]
# dt[, (names(dt)) := lapply(.SD, unlist), .SDcols = 1:ncol(dt)]
# names(dt) <- names(data_list[[1]])
# dt
#}
cleansingCorpus <- function(
htmlString, rem.html =TRUE, rem.http = TRUE, rem.newline = TRUE,
rem.nonalphanum = TRUE, rem.longwords = TRUE, rem.space = TRUE,
tolower = TRUE, add.space.to.numbers = TRUE, rem.country.begin = FALSE,
rem.nonalphanum.begin = FALSE, rem.space.begin = FALSE
){
if(rem.html){text <- gsub("<.*?>", " ", htmlString)} # removing html commands
if(rem.http){text <- gsub(" ?(f|ht)tp(s?)://(.*)[.][a-z]+", " ", text)} #removing http destinations
if(rem.newline){text <- gsub("[\r\n\t]", " ", text)}
if(rem.nonalphanum){text <- gsub("[^[:alpha:]]", " ", text)} #removing non-alphanumeric
if(rem.longwords){text <- gsub("\\w{35,}", " ", text)} ##Removing words with more than 30 letters
if(rem.space){text <- gsub("\\s+", " ", text)} #removing excess space
if(tolower){text <- tolower(text)}
if(add.space.to.numbers){ #add space between number and letters
text <- gsub("([0-9])([[:alpha:]])", "\\1 \\2", text)
text <- gsub("([[:alpha:]]|[.])([0-9])", "\\1 \\2", text)
}
if(rem.space.begin){text <- gsub("^[[:space:]]*", "", text)}
if(rem.country.begin){text <- gsub("^EU", "", text)} #remove country codes from the beginning of the text
if(rem.nonalphanum.begin){text <- gsub("^[?–-]*", "", text)} #remove special characters identified in the beginning of text
if(rem.space.begin){text <- gsub("^[[:space:]]*", "", text)}
trimws(text)
}
#This function removes dates that are "relics" from the xml parsing
removeDates <- function(text){
days <- "(Sunday,|Monday,|Tuesday,|Wednesday,|Thursday,|Friday,|Saturday,)"
months <- "(January|February|March|April|May|June|July|August|September|October|November|December|Months)"
date_form1 <- paste(days, months, "([0-9]|[0-9][0-9]), [0-9][0-9][0-9][0-9]")
date_form2 <- "\\?[0-9][0-9][0-9][0-9]"
text <- gsub(date_form1, " ", text)
gsub(date_form2, " ", text)
}
xmlToDataTable <- function(xmlData, itemNames){
itemList <- lapply(itemNames,
function(x){
xml_text(xml_find_all(xmlData, paste0(".//item/", x)))
}
)
names(itemList) <- xmlItems
as.data.table(itemList)
}
cleanCorpusHtml <- function(text){
unlist(lapply(text, function(x){
if(nchar(x) > 0){
# because nodes were starting with tag keywords in li, we relocate at the end so the information remains and the description
# starts with the main content
html <- gsub(">","> ", x) # add spaces after html tags so these aren't concatenated
xml <- read_xml(html, as_html = TRUE)
lis <- xml_find_all(xml, ".//li")
xml_remove(lis)
text <- paste( paste(xml_text(xml), collapse ="") , paste(xml_text(lis) , collapse =""), collapse ="")
text <- gsub("\\s+"," ", text)
}else {""}
}))
}
#Split equally a vector into chunks of number n_chunks
equal_split <- function(vct, n_chunks) {
lim <- length(vct)
fstep <- lim%/%n_chunks
idx_list <- list()
for(i in seq(n_chunks - 1)){
idx_list[[i]] <- vct[((i-1)*fstep + 1):(i*(fstep))]
}
idx_list[[n_chunks]] <- vct[((n_chunks - 1)*fstep + 1):(lim)]
return(idx_list)
}
#Function that takes a vector, and returns thresholded first 10 sorted indexes
getThresholdOrderRwmd <- function(vct, idVec, threshold = 1e-6, numHead = 10){
vct <- ifelse(vct > threshold, vct, Inf)
indexVec <- head(order(vct), numHead)
idVec[indexVec]
}
#Function to read xml nodes in description
maintainElements <- function(nodes, elementType = "a", attribute = "href"){
xml_attr(xml_find_all(nodes, paste0(".//", elementType)), attribute)
}
#Function to add results to datatable
elementsToDataTable <- function(result, elementType){
if(length(result) > 0)
data.table(elementType = elementType, attributeValue = result)
else
data.table()
}
#Function to retrieve urls from text
keepHtmlElements <- function(feedItem){
nodes <- read_xml(paste0("<div>", feedItem, "</div>"), as_html = TRUE)
rbind(
elementsToDataTable(maintainElements(nodes, "a", "href"), "link"),
elementsToDataTable(maintainElements(nodes, "img", "src"), "image"),
elementsToDataTable(maintainElements(nodes, "img-src", "src"), "image")
#All "img-src" are NA
)
}
#retrieve list of parameters in a http request query
getQueryParams <- function(url){
query <- httr::parse_url(url)$query
queryValues <- unlist(query)
queryNames <- names(query)
dat <- data.table(varName = queryNames, value = queryValues)
dat[queryValues != ""]
}
keepCountryName <- function(string){
string <- gsub(".*_", "", string)
gsub("\\..*", "", string)
}
keepNTokens <- function(string, num){
tokenList <- strsplit(string, split = " ")
sapply(tokenList, function(tokens){
tokens <- sort(tokens)
tokensShift <- shift(tokens, -num, fill = FALSE)
paste(tokens[tokens != tokensShift], collapse = " ")
})
}
findTFIDF <- function(corpus, stopwords, normalize = "double", min_char = 1) {
tokensList <- strsplit(corpus[, text], " ")
names(tokensList) <- corpus[, code]
tokensDT <- lapply(tokensList, as.data.table) %>%
rbindlist(idcol = TRUE) %>%
setnames(c("class", "term"))
tokensDT <- tokensDT[!term %in% stopwords][nchar(term) > min_char]
#inverse document frequency smooth
idfDT <- tokensDT[!duplicated(tokensDT)][, .(docFreq = .N), by = "term"]
idfDT[, idf := log(length(unique(tokensDT$class)) / (docFreq + 1)) + 1]
tfDT <- tokensDT[, .(term_count = .N), by = c("class", "term")]
if(normalize == "double")tfDT[, tf := 0.5 + 0.5 * term_count / max(term_count), by = "class"]
if(normalize == "log")tfDT[, tf := log(1 +term_count)]
merge(tfDT, idfDT, on = "term")[, tfIdf := tf*idf ][, .(term, class, tfIdf)]
}
############################################################################################################# R version 4.0.5 (2021-03-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] stringdist_0.9.6.3 text2vec_0.6 DT_0.18 magrittr_2.0.1
## [5] rmarkdown_2.8 data.table_1.14.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.6 mlapi_0.1.0 knitr_1.33
## [4] RhpcBLASctl_0.20-137 float_0.2-4 lattice_0.20-41
## [7] R6_2.5.0 rlang_0.4.11 lgr_0.4.2
## [10] stringr_1.4.0 highr_0.9 tools_4.0.5
## [13] grid_4.0.5 xfun_0.23 jquerylib_0.1.4
## [16] htmltools_0.5.1.1 yaml_2.2.1 digest_0.6.27
## [19] rsparse_0.4.0 crayon_1.4.1 Matrix_1.3-2
## [22] vctrs_0.3.8 sass_0.4.0 htmlwidgets_1.5.3
## [25] evaluate_0.14 stringi_1.6.2 compiler_4.0.5
## [28] bslib_0.2.5 jsonlite_1.7.2../000.core/00.02.base.functions.R completed in 0.12 seconds
inputRepo <- getSourcePath("jobsOutput/skills/skillsForMatching/")
filename <- "linguisticText.rds"
linguisticText <- loadBinary(filename, inputRepo)Type of data: data.table, data.frame.
Dimensions: 946312, 4.
Column Names: id, locale, label, index.
fileName <- "jobsOutput/skills/skillsListDtClean.rds"
allESCOskillsListClean <- loadBinary(fileName)Type of data: list.
Dimensions: ****.
Column Names: ar, bg, cs, da, de, el, en, es, et, fi, fr, ga, hr, hu, is, it, lt, lv, mt, nl, no, pl, pt, ro, sk, sl, sv.
01.00.load.data.R completed in 8.39 seconds
linguisticLocale <- linguisticText$locale %>% unique
validLocale <- linguisticLocale[linguisticLocale %in% names(allESCOskillsListClean)]
linguisticDataList <- lapply(validLocale, function(loc)linguisticText[locale == loc])
names(linguisticDataList) <- validLocale
matches <- lapply(validLocale, function(loc){
lookupUri <- keepSkillsList[[loc]]
linguisticData <- linguisticDataList[[loc]]
lookupMatch <- match(linguisticData$label, lookupUri$preferredLabel)
linguisticData[, suggestedCode := lookupUri$conceptUri[lookupMatch]]
}) %>% rbindlist## NULL02.00.process.data.R completed in 4.76 seconds
outputRepo <- getSourcePath("jobsOutput/skills/skillsForMatching/")
filename <- "linguisticTextSuggestedUri.rds"
saveBinary(matches[!is.na(suggestedCode)], filename, outputRepo)Datasource : /data/generic/jobsOutput/skills/skillsForMatching/linguisticTextSuggestedUri.rds of 13,530,081 bytes.
filename <- "nonMatchedLinguisticText.rds"
saveBinary(matches[is.na(suggestedCode)], filename, outputRepo)Datasource : /data/generic/jobsOutput/skills/skillsForMatching/nonMatchedLinguisticText.rds of 1,643,590 bytes.
03.00.save.data.R completed in 5.49 seconds
Completed in 20.78 seconds.