R/classify.R
classify_umu_ub.RdUmeå University provides a web api described here, for classifying english and swedish language records from DiVA or Swepub based on the MODS format (v 3.2 or later) according to the Swedish standard. Classification can also be made based on a Web of Science record Uploaded record batches may not exceed 200 MB, using batches of 10 MB are recommended (around 2-3000 records per chunk)
classify_umu_ub(
record,
type = c("mods", "wos"),
threshold = 0.2,
email = "foo.bar@null.se"
)string the publication identifier string in DiVA or an export file from Web of Science in the "Plain text/Full record" format
string, type of identifier, one of "mods" or "wos", default: "mods"
a value in between 0.1 and 0.51, which governs to which which extent a record is classified with more than one subject area
email adress for the user
a tibble with suggested classifications
The classification is based on information in there record from the title and abstract (required) but also on keywords, ISSN/journal, ISBN-prefix/ publisher and affiliations. Training data comes from SwePub (July 2020). It is based on the following papers:
Dual Coordinate Descent Methods for Logistic Regression and Maximum Entropy Models. (doi:10.1007/s10994-010-5221-8)
Entropy-Based Term Weighting Schemes for Text Categorization in VSM. (doi:10.1109/ICTAI.2015.57)
The classification is made at the research topic level (5 digits) for English language records and at research subject group level 3 digits for Swedish language records.
if (FALSE) { # \dontrun{
# classify using a DiVA record identifier
classify_umu_ub("diva2:515038", threshold = 0.3, email = "john.doe@hotmail.com")
# classify using a WoS Record in Flatfile/Plain text format
wos_record <- readr::read_lines("https://klassificera.ub.umu.se/uploadFile.txt")
classify_umu_ub(wos_record, type = "wos")
} # }