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A multi-scale local attention mechanism for aspect extraction [PDF]
Scientific ReportsAspect extraction is a critical step in constructing knowledge graphs and involves extracting aspect information from unstructured text. Current methods typically employ attention-based techniques such as global or local attention mechanisms, each with ...
Qian Yang +7 more
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Aspect extraction on user textual reviews using multi-channel convolutional neural network [PDF]
PeerJ Computer Science, 2019 Aspect extraction is a subtask of sentiment analysis that deals with identifying opinion targets in an opinionated text. Existing approaches to aspect extraction typically rely on using handcrafted features, linear and integrated network architectures ...
Aminu Da’u, Naomie Salim
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A supervised scheme for aspect extraction in sentiment analysis using the hybrid feature set of word dependency relations and lemmas. [PDF]
PeerJ Comput Sci, 2021 Due to the massive progression of the Web, people post their reviews for any product, movies and places they visit on social media. The reviews available on social media are helpful to customers as well as the product owners to evaluate their products ...
Bhamare BR, Prabhu J.
europepmc +2 more sources
Embarrassingly Simple Unsupervised Aspect Extraction [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 We present a simple but effective method for aspect identification in sentiment analysis. Our unsupervised method only requires word embeddings and a POS tagger, and is therefore straightforward to apply to new domains and languages. We introduce Contrastive Attention (CAt), a novel single-head attention mechanism based on an RBF kernel, which gives a ...
Stéphan Tulkens +1 more
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A Systematic Review on Implicit and Explicit Aspect Extraction in Sentiment Analysis
IEEE Access, 2020 Aspect-based sentiment analysis (ABSA) is currently among the most vigorous areas in natural language processing (NLP). Individuals, private and government institutions are increasingly using media sources for decision making.
Jaafar Zubairu Maitama +4 more
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Exploring BERT for Aspect Extraction in Portuguese Language
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 Sentiment Analysis is the computer science field that comprises techniques that aim to automatically extract opinions from texts. Usually, these techniques assign a Sentiment Orientation to the whole document (Document Level Sentiment Analysis).
Émerson Lopes +2 more
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Improving aspect-level sentiment analysis with aspect extraction
Neural Computing and Applications, 2020 Aspect-based sentiment analysis (ABSA), a popular research area in NLP, has two distinct parts—aspect extraction (AE) and labelling the aspects with sentiment polarity (ALSA). Although distinct, these two tasks are highly correlated. The work primarily hypothesizes that transferring knowledge from a pre-trained AE model can benefit the performance of ...
Navonil Majumder +4 more
semanticscholar +4 more sources
A More Fine-Grained Aspect–Sentiment–Opinion Triplet Extraction Task
Mathematics, 2023 Sentiment analysis aims to systematically study affective states and subjective information in digital text through computational methods. Aspect Sentiment Triplet Extraction (ASTE), a subtask of sentiment analysis, aims to extract aspect term, sentiment
Yuncong Li, Fang Wang, Sheng-hua Zhong
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Unsupervised Neural Aspect Extraction with Sememes [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Aspect extraction relies on identifying aspects by discovering coherence among words, which is challenging when word meanings are diversified and processing on short texts. To enhance the performance on aspect extraction, leveraging lexical semantic resources is a possible solution to such challenge.
Ling Luo +6 more
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Enhancing Aspect Extraction for Hindi [PDF]
Proceedings of The 4th Workshop on e-Commerce and NLP, 2021 Aspect extraction is not a well-explored topic in Hindi, with only one corpus having been developed for the task. In this paper, we discuss the merits of the existing corpus in terms of quality, size, sparsity, and performance in aspect extraction tasks using established models.
Arghya Bhattacharya +2 more
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