<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-QJWP31HF</identifier><date>2023</date><creator>Akram, Arwa</creator><creator>Sabir, Aliea</creator><relation>documents/doc/Q/URN_NBN_SI_doc-QJWP31HF_001.pdf</relation><relation>documents/doc/Q/URN_NBN_SI_doc-QJWP31HF_001.txt</relation><format format_type="volume">47</format><format format_type="issue">9</format><format format_type="type">article</format><format format_type="extent">str. 123-131</format><identifier identifier_type="DOI">10.31449/inf.v47i9.5217</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">210596867</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-QJWP31HF</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">analiza sentimenta</subject><subject language_type_id="slv">BERT</subject><subject language_type_id="slv">ekstrakcija vidikov</subject><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">umetna inteligenca</subject><title>Fine-tuning BERT for aspect extraction in multi-domain ABSA</title></Record>