| Autor: |
Wu, Linxiao, Luo, Yuanshuai, Zhu, Binrong, Liu, Guiran, Wang, Rui, Yu, Qian |
| Rok vydání: |
2024 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
Amidst the swift evolution of social media platforms and e-commerce ecosystems, the domain of opinion mining has surged as a pivotal area of exploration within natural language processing. A specialized segment within this field focuses on extracting nuanced evaluations tied to particular elements within textual contexts. This research advances a composite framework that amalgamates the positional cues of topical descriptors. The proposed system converts syntactic structures into a matrix format, leveraging convolutions and attention mechanisms within a graph to distill salient characteristics. Incorporating the positional relevance of descriptors relative to lexical items enhances the sequential integrity of the input. Trials have substantiated that this integrated graph-centric scheme markedly elevates the efficacy of evaluative categorization, showcasing preeminence. |
| Databáze: |
arXiv |
| Externí odkaz: |
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