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Hits 101 – 120 of 5.129

101
Differences in Chinese and Western tourists faced with Japanese hospitality: A natural language processing approach ...
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102
Zero-Shot Open Information Extraction using Question Generation and Reading Comprehension ...
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103
Knowledge Graph Completion with Text-aided Regularization ...
Chen, Tong; Zhu, Sirou; Wen, Yiming. - : arXiv, 2021
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104
Automatic extraction of requirements expressed in industrial standards : a way towards machine readable standards ? ...
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105
Can we aggregate human intelligence? an approach for human centric aggregation using ordered weighted averaging operators ...
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106
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies ...
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107
How to Query Language Models? ...
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108
Gender Recognition in Informal and Formal Language Scenarios via Transfer Learning ...
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109
Personalized Transformer for Explainable Recommendation ...
Li, Lei; Zhang, Yongfeng; Chen, Li. - : arXiv, 2021
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110
Learning Relation Alignment for Calibrated Cross-modal Retrieval ...
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111
Document Domain Randomization for Deep Learning Document Layout Extraction ...
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112
SIGIR 2021 E-Commerce Workshop Data Challenge ...
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113
Linguistically Informed Masking for Representation Learning in the Patent Domain ...
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114
Improving Authorship Verification using Linguistic Divergence ...
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115
BIOPAK Flasher: Epidemic disease monitoring and detection in Pakistan using text mining ...
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116
Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings ...
Abstract: We propose a method for online news stream clustering that is a variant of the non-parametric streaming K-means algorithm. Our model uses a combination of sparse and dense document representations, aggregates document-cluster similarity along these multiple representations and makes the clustering decision using a neural classifier. The weighted document-cluster similarity model is learned using a novel adaptation of the triplet loss into a linear classification objective. We show that the use of a suitable fine-tuning objective and external knowledge in pre-trained transformer models yields significant improvements in the effectiveness of contextual embeddings for clustering. Our model achieves a new state-of-the-art on a standard stream clustering dataset of English documents. ... : To appear in Proceedings of The 16th Conference of the European Chapter of the Association for Computational Linguistics ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; I.2.7; Information Retrieval cs.IR
URL: https://arxiv.org/abs/2101.11059
https://dx.doi.org/10.48550/arxiv.2101.11059
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117
On the Calibration and Uncertainty of Neural Learning to Rank Models ...
Penha, Gustavo; Hauff, Claudia. - : arXiv, 2021
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118
MULTIMODAL ANALYSIS: Informed content estimation and audio source separation ...
Meseguer-Brocal, Gabriel. - : arXiv, 2021
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119
Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval ...
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120
A Linguistic Study on Relevance Modeling in Information Retrieval ...
Fan, Yixing; Guo, Jiafeng; Ma, Xinyu. - : arXiv, 2021
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