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Glacier boundary extraction and spatiotemporal variation analysis in Geladandong region. [PDF]

PeerJ
Liu H, Wang D, Li T, Yue A, Zhao S, Zhang L, Ye K, Zhang H, Ji S.   +8 more
europepmc   +1 more source

Landslide Hazard Identification and Prediction in Complex Mountainous Areas Using Ascending and Descending Orbits InSAR Technology. [PDF]

Sensors (Basel)
Zhao W, Cong P, Ma X, Yi M, Liu C, Gao J, Zhang Y.   +6 more
europepmc   +1 more source

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Multi-task learning for aspect term extraction and aspect sentiment classification

Neurocomputing, 2020
Abstract 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, Asif Ekbal
exaly   +2 more sources

Syntax-Aware Representation for Aspect Term Extraction

Lecture Notes in Computer Science, 2019
Aspect Term Extraction (ATE) plays an important role in aspect-based sentiment analysis. Syntax-based neural models that learn rich linguistic knowledge have proven their effectiveness on ATE. However, previous approaches mainly focus on modeling syntactic structure, neglecting rich interactions along dependency arcs. Besides, these methods highly rely
Xian Sun
exaly   +2 more sources

A hybrid unsupervised method for aspect term and opinion target extraction

Knowledge-Based Systems, 2018
Abstract Aspect term extraction (ATE) and opinion target extraction (OTE) are two important tasks in fine-grained sentiment analysis field. Existing approaches to ATE and OTE are mainly based on rules or machine learning methods. Rule-based methods are usually unsupervised, but they can’t make use of high level features.
Chuhan Wu, Fangzhao Wu, Zhigang Yuan
exaly   +2 more sources

Post-processing method with aspect term error correction for enhancing aspect term extraction

Applied Intelligence, 2022
Ruyan Wang, Rongjian Zhao, Zhigang Yang   +2 more
exaly   +2 more sources

Constituency Lattice Encoding for Aspect Term Extraction

Proceedings of the 28th International Conference on Computational Linguistics, 2020
One 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, Kun Li 0003, Xiaojun Quan, Weizhou Shen, Qinliang Su   +4 more
openaire   +1 more source

A span-based model for aspect terms extraction and aspect sentiment classification

Neural Computing and Applications, 2020
Sentiment analysis is a field of natural language processing, which is used to identify and extract opinions and attitudes from text. Aspect-based sentiment analysis aims to extract aspect terms and predict sentiment categories of the opinion aspects. It includes two subtasks: aspect terms extraction and aspect sentiment classification.
Yanxia Lv, Fangna Wei, Ying Zheng, Cong Wang 0009, Cong Wan, Cuirong Wang   +5 more
openaire   +1 more source

Self-augmented sequentiality-aware encoding for aspect term extraction

Information Processing and Management
Qingting Xu, Yu Hong, Chen Chen
exaly   +2 more sources