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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 23 1 Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks Liang, Bin; Su, Hang; Gui, Lin. - : Elsevier, 2022 BASE Show details 2 Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies ... Pergola, Gabriele; Kochkina, Elena; Gui, Lin. - : arXiv, 2021 BASE Show details 3 Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Gui, Lin; He , Yulan. - : Underline Science Inc., 2021 BASE Show details 4 Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Gui, Lin; He , Yulan. - : Underline Science Inc., 2021 BASE Show details 5 Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gui, Lin; Liang, Bin. - : Underline Science Inc., 2021 BASE Show details 6 Topic-driven and knowledge-aware transformer for dialogue emotion detection Zhu, Lixing; Pergola, Gabriele; Gui, Lin. - : Association for Computational Linguistics, 2021 BASE Show details 7 A disentangled adversarial neural topic model for separating opinions from plots in user reviews Pergola, Gabriele; Gui, Lin; He, Yulan. - : Association for Computational Linguistics, 2021 BASE Show details 8 Multi-modal sarcasm detection with interactive in-modal and cross-modal graphs Liang, Bin; Lou, Chenwei; Li, Xiang. - : ACM, 2021 BASE Show details 9 A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews ... Pergola, Gabriele; Gui, Lin; He, Yulan. - : arXiv, 2020 BASE Show details 10 CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering ... The 28th International Conference on Computational Linguistics 2020; Gui, Lin; He , Yulan. - : Underline Science Inc., 2020 BASE Show details 11 Jointly learning aspect-focused and inter-aspect relations with graph convolutional networks for aspect sentiment analysis Liang, Bin; Yin, Rongdi; Gui, Lin; Du, Jiachen; Xu, Ruifeng. - : International Committee on Computational Linguistics, 2020 Abstract: In this paper, we explore a novel solution of constructing a heterogeneous graph for each instance by leveraging aspect-focused and inter-aspect contextual dependencies for the specific aspect and propose an Interactive Graph Convolutional Networks (InterGCN) model for aspect sentiment analysis. Specifically, an ordinary dependency graph is first constructed for each sentence over the dependency tree. Then we refine the graph by considering the syntactical dependencies between contextual words and aspect-specific words to derive the aspect-focused graph. Subsequently, the aspect-focused graph and the corresponding embedding matrix are fed into the aspect-focused GCN to capture the key aspect and contextual words. Besides, to interactively extract the inter-aspect relations for the specific aspect, an inter-aspect GCN is adopted to model the representations learned by aspect-focused GCN based on the inter-aspect graph which is constructed by the relative dependencies between the aspect words and other aspects. Hence, the model can be aware of the significant contextual and aspect words when interactively learning the sentiment features for a specific aspect. Experimental results on four benchmark datasets illustrate that our proposed model outperforms state-of-the-art methods and substantially boosts the performance in comparison with BERT. Keyword: QA76 Electronic computers. Computer science. Computer software URL: http://wrap.warwick.ac.uk/149293/1/WRAP-jointly-learning-aspect-focused-inter-aspect-relations-graph-convolutional-networks-aspect-sentiment-analysis-Gui-2020.pdf https://doi.org/10.18653/v1/2020.coling-main.13 http://wrap.warwick.ac.uk/149293/ BASE Hide details 12 Commonsense knowledge enhanced memory network for stance classification Du, Jiachen; Gui, Lin; Xu, Ruifeng. - : IEEE Computer Society, 2020 BASE Show details 13 Transition-based directed graph construction for emotion-cause pair extraction Fan, Chuang; Yang, Min; Du, Jiachen. - : Association for Computational Linguistics, 2020 BASE Show details 14 A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ... Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019 BASE Show details 15 A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ... Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019 BASE Show details 16 TDAM: a topic-dependent attention model for sentiment analysis Pergola, Gabriele; Gui, Lin; He, Yulan. - : Elsevier, 2019 BASE Show details 17 A knowledge regularized hierarchical approach for emotion cause analysis Gui, Lin; Bing, Lidong; Xu, Ruifeng. - : Association for Computational Linguistics, 2019 BASE Show details 18 Neural topic model with reinforcement learning Zhou, Yu; Gui, Lin; Xu, Ruifeng. - : Association for Computational Linguistics, 2019 BASE Show details 19 A Question Answering Approach to Emotion Cause Extraction ... Gui, Lin; Hu, Jiannan; He, Yulan. - : arXiv, 2017 BASE Show details 20 A question answering approach for emotion cause extraction Gui, Lin; Hu, Jiannan; He, Yulan. - : Association for Computational Linguistics, 2017 BASE Show details Page: 1 2

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