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Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T

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Palgrave Frontiers in Philosophy of Religionchoosing key semantic vectors to guide the response generation. Based on the structured semantics, it also develops a calibration mechanism with a dynamic vocabulary during decoding, which enhances exact coherent expressions by adjusting word distribution. According to the experiments, ConDial shows
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Palgrave Frontiers in Philosophy of Religionrom refined word representations through fully connected layers. Moreover, we propose a triangle distance loss function for embedding layers as an auxiliary task to obtain discriminative representations. It is optimized jointly with pairwise ranking loss for ad hoc document ranking task. Experimenta
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Zhongwei Zhao,Wei Chen,Yongai Jins (AAN) to learn the domain-invariant and discriminative features simultaneously based on Maximum Mean Discrepancy (MMD) and CMD. Meanwhile, to trade off between the marginal and conditional distributions, we further maximize both MMD and CMD criterions using adversarial strategy to make the feature
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Zhongwei Zhao,Wei Chen,Yongai Jinte-of-the-art filter methods for text feature selection and conduct experiments on two datasets: Reuters-21578 and WebKB. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are taken as the subsequent classifiers. Experimental results shows that the proposed DMI has significantly improved the
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Understanding Fertility Trends in China history questions and answers are encoded into the contexts for the multi-turn setting. To capture the task-level importance of different layer outputs, a task-specific attention layer is further added to the CAT-BERT outputs, reflecting the positions that the model should pay attention to for a sp
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Silindiwe Zvingowanisei,Sophia Chirongomaration Search approach by Shared Structure encoding for neural-based Multi-Task models (TGG-S3MT). The experiments based on the real text datasets with multiple text mining tasks show that SSE is effective for formulating the multi-task architecture search. Moreover, both .-S4MT and TGG-S3MT have be
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Automated Context-Aware Phrase Mining from Text Corporaity phrases effectively. 2) an instance selection network that focuses on choosing correct sentences with reinforcement learning for further improving the prediction performance of phrase recognition network. Experimental results demonstrate that our ConPhrase outperforms the state-of-the-art approa
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