FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3043133652> ?p ?o ?g. }

• W3043133652 endingPage "128855" @default.
• W3043133652 startingPage "128845" @default.
• W3043133652 abstract "Despite the great manufactures' efforts to achieve customer satisfaction and improve their performance, social media opinion mining is still on the fly a big challenge. Current opinion mining requires sophisticated feature engineering and syntactic word embedding without considering semantic interaction between aspect term and opinionated features, which degrade the performance of most of opinion mining tasks, especially those that are designed for smart manufacturing. Research on intelligent aspect level opinion mining (AOM) follows the fast proliferation of user-generated data through social media for industrial manufacturing purposes. Google's pre-trained language model, Bidirectional Encoder Representations from Transformers (BERT) widely overcomes existing methods in eleven natural language processing (NLP) tasks, which makes it the standard way for semantic text representation. In this paper, we introduce a novel deep learning model for fine-grained aspect-based opinion mining, named as FGAOM. First, we train the BERT model on three specific domain corpora for domain adaption, then use adjusted BERT as embedding layer for concurrent extraction of local and global context features. Then, we propose Multi-head Self-Attention (MSHA) to effectively fuse internal semantic text representation and take advantage of convolutional layers to model aspect term interaction with surrounding sentiment features. Finally, the performance of the proposed model is evaluated via extensive experiments on three public datasets. Results show that performance of the proposed model outperforms performances of recent the-of-the-art models." @default.
• W3043133652 created "2020-07-23" @default.
• W3043133652 creator A5006366563 @default.
• W3043133652 creator A5013355587 @default.
• W3043133652 creator A5045379886 @default.
• W3043133652 creator A5048666024 @default.
• W3043133652 date "2020-01-01" @default.
• W3043133652 modified "2023-10-14" @default.
• W3043133652 title "Deep Learning Model for Fine-Grained Aspect-Based Opinion Mining" @default.
• W3043133652 cites W2251124635 @default.
• W3043133652 cites W2252057809 @default.
• W3043133652 cites W2342662179 @default.
• W3043133652 cites W2556536142 @default.
• W3043133652 cites W2899232971 @default.
• W3043133652 cites W2909211416 @default.
• W3043133652 cites W2943796356 @default.
• W3043133652 cites W2949619369 @default.
• W3043133652 cites W2953751391 @default.
• W3043133652 cites W2955260208 @default.
• W3043133652 cites W2960680116 @default.
• W3043133652 cites W2964671814 @default.
• W3043133652 cites W2969743835 @default.
• W3043133652 cites W2971559111 @default.
• W3043133652 cites W2971586182 @default.
• W3043133652 cites W2973325524 @default.
• W3043133652 cites W2979860911 @default.
• W3043133652 cites W2979872739 @default.
• W3043133652 cites W2980481399 @default.
• W3043133652 cites W2982225079 @default.
• W3043133652 cites W2985244827 @default.
• W3043133652 cites W2988032913 @default.
• W3043133652 cites W2991675023 @default.
• W3043133652 cites W2993821971 @default.
• W3043133652 cites W2995071747 @default.
• W3043133652 cites W2998964503 @default.
• W3043133652 cites W2999375771 @default.
• W3043133652 cites W3000546628 @default.
• W3043133652 cites W3001093415 @default.
• W3043133652 cites W3001321893 @default.
• W3043133652 cites W3003580126 @default.
• W3043133652 cites W3003618396 @default.
• W3043133652 cites W3005043037 @default.
• W3043133652 cites W3005328069 @default.
• W3043133652 cites W3011249019 @default.
• W3043133652 cites W3104455619 @default.
• W3043133652 doi "https://doi.org/10.1109/access.2020.3008824" @default.
• W3043133652 hasPublicationYear "2020" @default.
• W3043133652 type Work @default.
• W3043133652 sameAs 3043133652 @default.
• W3043133652 citedByCount "18" @default.
• W3043133652 countsByYear W30431336522021 @default.
• W3043133652 countsByYear W30431336522022 @default.
• W3043133652 countsByYear W30431336522023 @default.
• W3043133652 crossrefType "journal-article" @default.
• W3043133652 hasAuthorship W3043133652A5006366563 @default.
• W3043133652 hasAuthorship W3043133652A5013355587 @default.
• W3043133652 hasAuthorship W3043133652A5045379886 @default.
• W3043133652 hasAuthorship W3043133652A5048666024 @default.
• W3043133652 hasBestOaLocation W30431336521 @default.
• W3043133652 hasConcept C108583219 @default.
• W3043133652 hasConcept C111919701 @default.
• W3043133652 hasConcept C118505674 @default.
• W3043133652 hasConcept C136764020 @default.
• W3043133652 hasConcept C154945302 @default.
• W3043133652 hasConcept C195324797 @default.
• W3043133652 hasConcept C204321447 @default.
• W3043133652 hasConcept C2777462759 @default.
• W3043133652 hasConcept C2778827112 @default.
• W3043133652 hasConcept C2779439875 @default.
• W3043133652 hasConcept C41008148 @default.
• W3043133652 hasConcept C41608201 @default.
• W3043133652 hasConcept C518677369 @default.
• W3043133652 hasConcept C59404180 @default.
• W3043133652 hasConcept C66402592 @default.
• W3043133652 hasConceptScore W3043133652C108583219 @default.
• W3043133652 hasConceptScore W3043133652C111919701 @default.
• W3043133652 hasConceptScore W3043133652C118505674 @default.
• W3043133652 hasConceptScore W3043133652C136764020 @default.
• W3043133652 hasConceptScore W3043133652C154945302 @default.
• W3043133652 hasConceptScore W3043133652C195324797 @default.
• W3043133652 hasConceptScore W3043133652C204321447 @default.
• W3043133652 hasConceptScore W3043133652C2777462759 @default.
• W3043133652 hasConceptScore W3043133652C2778827112 @default.
• W3043133652 hasConceptScore W3043133652C2779439875 @default.
• W3043133652 hasConceptScore W3043133652C41008148 @default.
• W3043133652 hasConceptScore W3043133652C41608201 @default.
• W3043133652 hasConceptScore W3043133652C518677369 @default.
• W3043133652 hasConceptScore W3043133652C59404180 @default.
• W3043133652 hasConceptScore W3043133652C66402592 @default.
• W3043133652 hasLocation W30431336521 @default.
• W3043133652 hasOpenAccess W3043133652 @default.
• W3043133652 hasPrimaryLocation W30431336521 @default.
• W3043133652 hasRelatedWork W2726375170 @default.
• W3043133652 hasRelatedWork W2773312050 @default.
• W3043133652 hasRelatedWork W2785740378 @default.
• W3043133652 hasRelatedWork W2912503608 @default.
• W3043133652 hasRelatedWork W3015724364 @default.
• W3043133652 hasRelatedWork W3164948662 @default.

• next