International Journal of Computational and Experimental Science and Engineering, Год журнала: 2025, Номер 11(2)
Опубликована: Апрель 16, 2025
Social media plays a pivotal role in people’s daily lives where users distribute diverse materials and subjects like ideas, events, emotions. As the number of people grows, extensive use social platforms has resulted creation vast amounts information. These unstructured data need to be labelled for understanding relevant information that aids various applications such as healthcare, entertainment even sentimental politics. have large labels which needs brighter light annotation tags document with most labels. Extreme Multi-Label Classification (XMTC) aims solve above problem by automatically labelling file pertinent label from buckets sets. Because surge big data, implementing XMTC become significant challenge handle millions features This bottleneck was overshadowed arrival Machine Learning (ML) Deep (DL) algorithms. But computational overhead training these learning networks degrades performance handling larger data. To this aforementioned problem, research paper proposes ensemble combination Dolphin Optimized Hybrid classification networks. The proposed model comprises triple set: Initially, it incorporates multi-label dolphin optimized procedure recognize weight every word relation structure details are utilized ascertain link among phrases compress Finally, label-aware formulated Stacked Gated Recurrent Feed Forward attain final massive documents. comprehensive experimentation is carried out using EuroLeX benchmarks metrics accuracy, precision, recall, hamming score calculated. prove excellence recommended varied state-of-the art models, Results demonstrates exhibited superior over models notably on tail
Язык: Английский