id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_qrknnrsfj5d3xinxeligze6g4i	Lucía Santamaría	Comparison and benchmark of name-to-gender inference services	2018	29	.pdf	application/pdf	15201	1491	62	We compare and benchmark five nameto-gender inference services by applying them to the classification of a test data set assign a gender to 73% of authors with full first names by using data from the US Social Figure 1 Geographical region of origin of the personal names from our test data set as inferred by working instead with the 5,779 names in our data set which possess a defined gender label. API, and genderize.io to assign genders to all names in our test data set. Table 4 Benchmark 1a: performance metrics for all services with their default gender assignments on the entire data set. Table 6 Benchmark 1b, data source: Performance of all services with their default gender assignments in terms of the metrics errorCoded and Gender API is the best performing service on all data sets; of available gender inference tools, testing five services on a manually labeled data set	./cache/work_qrknnrsfj5d3xinxeligze6g4i.pdf	./txt/work_qrknnrsfj5d3xinxeligze6g4i.txt