Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training (D19-1)
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| Challenge: | Current weakly supervised approaches for learning aspect classifiers require many fine-grained aspect labels, which are labor-intensive to obtain. |
| Approach: | They propose a weakly supervised approach that leverages seed words for aspect detection . they propose supervised student-teacher approach that uses teacher to train student models . |
| Outcome: | The proposed approach outperforms previous weakly supervised approaches by 14.1 F1 points on average in six domains of product reviews and six multilingual datasets of restaurant reviews. |
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| Challenge: | Existing methods for aspect detection use seed words as priors or features of topic models. |
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| Challenge: | Recent work has focused on learning embedding spaces for seed words and sentences to establish similarities between sentences and aspects. |
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| Challenge: | Existing methods for aspect-based sentiment analysis of review text use only a few keywords describing each aspect/sentiment without using any labeled examples. |
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AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis (2022.emnlp-main)
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| Challenge: | Existing weakly supervised learning frameworks are used for segment classification . lack of segment labels prevents the use of standard supervised methods . |
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| Challenge: | Existing methods for weakly supervised text classification generate pseudo-labels in a context-free manner, thus, the ambiguous, context-dependent nature of human language has been long overlooked. |
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Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction (P18-2)
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| Challenge: | Recent supervised deep learning models have achieved state-of-the-art performance, but there are two other considerations that are important. |
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Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction (2020.findings-emnlp)
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| Challenge: | Aspect-oriented Fine-grained Opinion Extraction (AFOE) aims to extract aspect terms and opinion terms from review text in the form of opinion pairs or opinion triplets. |
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Aspect-Based Sentiment Analysis as Fine-Grained Opinion Mining (2020.lrec-1)
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| Challenge: | a large body of research has been done on aspect-based sentiment analysis (ABSA) for almost two decades . aspect-Based sentiment analysis is a task that extracts sentiment/opinions from text in terms of targets . |
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Neural Aspect and Opinion Term Extraction with Mined Rules as Weak Supervision (P19-1)
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| Challenge: | Lack of labeled training data is a major bottleneck for aspect and opinion term extraction . et al., 2004: aspect and opinions are of particular importance for opinion mining . |
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