The article discusses an approach to information extraction using onlinelearning based on determining the semantic proximity of sentence vectors and knowledge baseentities using neural network language models trained without a teacher on a large text corpusof the subject area. A detailed review of modern supervised and unsupervised informationextraction methods is provided, which allow achieving acceptable quality in solving the problemof analyzing current labor market requirements without the labor-intensive procedure of textcorpus tagging and without using rule-based approaches.
| Mualliflar | Doshanova M.Y.,, Otaxanova B.I.,, Aliyev R.R. |
|---|---|
| Jurnal | Management and Economics Scientific Research Journal |
| Nashr sanasi | 2025-04-18 |
| Jild | 2 |
| Son | 2 |
| Betlar | 10-22 |
| Til | Ingliz |
| DOI | 10.65152/mesr.v2i1-maxsus.78 |
DOI: 10.65152/mesr.v2i1-maxsus.78 · Maqolaning asl sahifasi
classification method, machine learning, neural network language models, natural language processing, information extraction, entity recognition.
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