Results 131 to 140 of about 448,200 (183)
Some of the next articles are maybe not open access.
Multi-task learning for aspect term extraction and aspect sentiment classification
Neurocomputing, 2020Abstract Aspect sentiment classification has a dependency over the aspect term extraction. The majority of the existing studies tackle these two problems independently, i.e., while performing aspect sentiment classification, it is assumed that the aspect terms are pre-identified. However, such assumptions are neither practical nor appropriate.
Md Shad Akhtar, Tarun Garg, Asif Ekbal
semanticscholar +4 more sources
Data Augmentation via Back-translation for Aspect Term Extraction
2023 International Joint Conference on Neural Networks (IJCNN), 2023We tackle Aspect Term Extraction (ATE), a task that automatically recognizes aspect terms conditioned on the under-standing of word-level semantics. Due to the capacity of enriching linguistic phenomena for learning, data augmentation contributes to the ...
Qingting Xu +4 more
openaire +2 more sources
Aspect Term Extraction Based on BiLSTM-CRF Model
2022 IEEE/ACIS 22nd International Conference on Computer and Information Science (ICIS), 2022Aspect term extraction is an important subtask in aspect sentiment analysis, and it is a necessary step to complete other subtasks. Existing studies focus on complex and changeable models and only use single dataset for training, which is not conducive ...
Jiazhao Chai +2 more
openaire +2 more sources
Constituency Lattice Encoding for Aspect Term Extraction
Proceedings of the 28th International Conference on Computational Linguistics, 2020One of the remaining challenges for aspect term extraction in sentiment analysis resides in the extraction of phrase-level aspect terms, which is non-trivial to determine the boundaries of such terms. In this paper, we aim to address this issue by incorporating the span annotations of constituents of a sentence to leverage the syntactic information in ...
Yunyi Yang +4 more
openaire +2 more sources
Context-Aware Dynamic Word Embeddings for Aspect Term Extraction
IEEE Transactions on Affective ComputingThe aspect term extraction (ATE) task aims to extract aspect terms describing a part or an attribute of a product from review sentences. Most existing works rely on either general or domain embedding to address this problem. Despite the promising results,
Jingyun Xu +6 more
openaire +2 more sources
Aspect term extraction for opinion mining using a Hierarchical Self-Attention Network
Neurocomputing, 2021Aspect identification is one of the important sub-tasks in opinion mining and this task can be considered as a token-level sequencing problem. Most recent approaches employ BERT based network to identify the aspect term, which is often complex, consumes ...
Avinash Kumar +5 more
semanticscholar +3 more sources
Aspect Term Extraction via Contrastive Learning over Self-augmented Data
2022 International Joint Conference on Neural Networks (IJCNN), 2022Aspect Term Extraction (ATE) is a natural language processing task, which identifies the languages describing product attributes. Such languages (words) are referred to aspect terms in this field.
Yuchen Pan +4 more
openaire +2 more sources
STC: Stacked Two-stage Convolution for Aspect Term Extraction
2021 International Symposium on Electrical, Electronics and Information Engineering, 2021Aspect term extraction (ATE) aims to extract aspect terms from reviews as opinion targets for sentiment analysis. Although some of the previous works prove that dependency relationship between aspect terms and context is useful for ATE, they have barely tried to use graph neural networks to capture valuable information in dependency patterns ...
Ruiqi Wang +3 more
openaire +2 more sources