Results 1 to 10 of about 6,578,111 (187)
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 ...
Tulkens, Stéphan +1 more
openaire +6 more sources
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
openaire +2 more sources
Explicit aspect extraction techniques: Review
Journal of Al-Qadisiyah for Computer Science and Mathematics, 2022 Sentiment analysis is gathering opinion keywords, such as aspects, opinions, or features- and figuring out their semantic perspective relations. More specifically, aspect-based sentiment analysis – (ABSA) is a subfield of natural language that focuses on phrases associated with aspects and detects the sentiment that belongs to each one.
Arwa Akram, Aliea Salman Sabir
openaire +2 more sources
Aspect extraction on user textual reviews using multi-channel convolutional neural network. [PDF]
PeerJ Comput Sci, 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 ...
Da'u A, Salim N.
europepmc +2 more sources
Lifelong Learning CRF for Supervised Aspect Extraction [PDF]
Annual Meeting of the Association for Computational Linguistics, 2017 This paper makes a focused contribution to supervised aspect extraction. It shows that if the system has performed aspect extraction from many past domains and retained their results as knowledge, Conditional Random Fields (CRF) can leverage this ...
Liu, Bing, Shu, Lei, Xu, Hu
core +2 more sources
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
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations [PDF]
arXiv.org, 2023 Existing aspect extraction methods mostly rely on explicit or ground truth aspect information, or using data mining or machine learning approaches to extract aspects from implicit user feedback such as user reviews.
Pan Li +3 more
semanticscholar +1 more source
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs [PDF]
International Conference on Information and Knowledge Management, 2022 The extraction of aspect terms is a critical step in fine-grained sentiment analysis of text. Existing approaches for this task have yielded impressive results when the training and testing data are from the same domain.
Phillip Howard +7 more
semanticscholar +1 more source
DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 The rise of pre-trained language models has yielded substantial progress in the vast majority of Natural Language Processing (NLP) tasks. However, a generic approach towards the pre-training procedure can naturally be sub-optimal in some cases ...
Entony Lekhtman +2 more
semanticscholar +1 more source