Recruitment scam detection using gated recurrent unit
| bracu.type.group | Research Publications | |
| datacite.rights | Metadata Only | |
| dc.contributor.author | Nessa, Iffatun | |
| dc.contributor.author | Zabin, Benozir | |
| dc.contributor.author | Faruk, Kazi Omar | |
| dc.contributor.author | Rahman, Anika | |
| dc.contributor.author | Nahar, Khairun | |
| dc.contributor.author | Iqbal, Shadab | |
| dc.contributor.author | Hossain, Md Sabbir | |
| dc.contributor.author | Mehedi, Md Humaion Kabir | |
| dc.contributor.author | Rasel, Annajiat Alim | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2026-08-15T12:16:23Z | |
| dc.date.available | 2026-08-15T12:16:23Z | |
| dc.date.issued | 2022-01-01 | |
| dc.description.abstract | Recruitment advertisements in-cluding fake or fraudulent job advertisements is delivered to any job seekers and lead them to lose their money or personal information by frauds. With mass digitization and inter-net access scammers are coming up with new ideas and recruitment fraud is one of them. By sending false recruitment emails, SMS texts, fake websites, fake social media profiles, fake job posts, online recruiting services such as LinkedIn, or unsolicited emails purporting to be from well-known organizations are common methods of recruitment fraud. To identify fake or fraudulent job advertisements, we have pro-posed a one layer gated recurrent unit (GRU) model that can classify scams and real re-cruitments. We also evaluate the efficiency and achieved 93.51% of AUC score on Employment Scam Aegean Dataset (EMSCAD) dataset. | |
| dc.description.version | Published | |
| dc.format.extent | 445-449 | |
| dc.identifier.citation | I. Nessa et al., "Recruitment Scam Detection Using Gated Recurrent Unit," 2022 IEEE 10th Region 10 Humanitarian Technology Conference (R10-HTC), Hyderabad, India, 2022, pp. 445-449, doi: 10.1109/R10-HTC54060.2022.9929928. | |
| dc.identifier.doi | 10.1109/R10-HTC54060.2022.9929928 | |
| dc.identifier.isbn | 9781665401562 | |
| dc.identifier.issn | 25727621 | |
| dc.identifier.other | 2-s2.0-85142113787 | |
| dc.identifier.uri | https://hdl.handle.net/10361/29083 | |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.hasversion | 10.1109/R10-HTC54060.2022.9929928 | |
| dc.relation.ispartof | IEEE Region 10 Humanitarian Technology Conference R10 Htc | |
| dc.relation.ispartofseries | IEEE Region 10 Humanitarian Technology Conference R10 Htc | |
| dc.relation.uri | https://ieeexplore.ieee.org/document/9929928 | |
| dc.rights | false | |
| dc.subject | GRU | |
| dc.subject | Machine learning | |
| dc.subject | NLP | |
| dc.subject | Recruitment scam | |
| dc.subject | Word embedding | |
| dc.subject.lcsh | Online social networks. | |
| dc.subject.lcsh | Machine learning. | |
| dc.title | Recruitment scam detection using gated recurrent unit | |
| dc.type | Conference Proceeding | |
| oaire.citation.volume | 2022-September | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.identifier.scopus-author-id | 57967865500 | |
| person.identifier.scopus-author-id | 57968329100 | |
| person.identifier.scopus-author-id | 57927317000 | |
| person.identifier.scopus-author-id | 58280892900 | |
| person.identifier.scopus-author-id | 57968639000 | |
| person.identifier.scopus-author-id | 57968942200 | |
| person.identifier.scopus-author-id | 57422733600 | |
| person.identifier.scopus-author-id | 57422283000 | |
| person.identifier.scopus-author-id | 56495276900 |