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Towards information-rich, logical text generation with knowledge-enhanced neural models [article]

Hao Wang, Bin Guo, Wei Wu, Zhiwen Yu
2020 arXiv   pre-print
However, existing end-to-end neural models suffer from the problem of tending to generate uninformative and generic text because they cannot ground input context with background knowledge.  ...  The challenges of knowledge enhanced text generation including how to select the appropriate knowledge from large-scale knowledge bases, how to read and understand extracted knowledge, and how to integrate  ...  Neural network models need input data with vector form, while the information stored in structured KB is symbolized.  ... 
arXiv:2003.00814v1 fatcat:5fllyakwqzf4vnmar3a6zjoewe

Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction

Jun Long, Lei Liu, Hongxiao Fei, Yiping Xiang, Haoran Li, Wenti Huang, Liu Yang
2022 Mathematics  
However, most existing relation extraction models ignore the semantic guidance of contextual information to entity mentions and treat entity mentions in and the textual context of a sentence equally.  ...  This model develops a self-attention enhanced neural network to concentrate on the importance and relevance of different words to obtain semantic-guided contextual information.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math10081344 fatcat:oml3xksrnbcqlawblneosygfv4

Construction and Application of Text Entity Relation Joint Extraction Model Based on Multi-Head Attention Neural Network

Yafei Xue, Jing Zhu, Jing Lyu, Gengxin Sun
2022 Computational Intelligence and Neuroscience  
Entity relationship extraction is one of the key areas of information extraction and is an important research content in the field of natural language processing.  ...  Based on the BERT training model architecture, this paper extracts textual entities and relations tasks.  ...  joint model of entity recognition and relation extraction for the input sentence. is joint model can overcome the shortcomings of the above serial method, and it follows that the model may have a more  ... 
doi:10.1155/2022/1530295 pmid:35655501 pmcid:PMC9155959 fatcat:ch24cpgqsvarnbyd24nqsvenjy

Making Document-Level Information Extraction Right for the Right Reasons [article]

Liyan Tang, Dhruv Rajan, Suyash Mohan, Abhijeet Pradhan, R. Nick Bryan, Greg Durrett
2022 arXiv   pre-print
Document-level models for information extraction tasks like slot-filling are flexible: they can be applied to settings where information is not necessarily localized in a single sentence.  ...  This work studies how to ensure that these models make correct inferences from complex text and make those inferences in an auditable way: beyond just being right, are these models "right for the right  ...  Thanks to Scott Rudkin, Gregory Mittl, Raghav Mattay, and Chuan Liang for assistance with the annotation.  ... 
arXiv:2110.07686v2 fatcat:st5aretytjdspgbfnkwkzfdezu

REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction [article]

Sheng Zhang, Patrick Ng, Zhiguo Wang, Bing Xiang
2022 arXiv   pre-print
Relation extraction is an important but challenging task that aims to extract all hidden relational facts from the text.  ...  In this work, we propose a knowledge-enhanced generative model to mitigate these two issues.  ...  Knowledge-Enhancement We leverage an entity linking model to ground texts to knowledge bases. In the Relation Classification task, the span of an entity E pos is given.  ... 
arXiv:2206.05123v2 fatcat:zdm6hq75rbb4ra3lgtwsgzlpte

Noise Robust TTS for Low Resource Speakers using Pre-trained Model and Speech Enhancement [article]

Dongyang Dai, Li Chen, Yuping Wang, Mu Wang, Rui Xia, Xuchen Song, Zhiyong Wu, Yuxuan Wang
2020 arXiv   pre-print
In this paper, the proposed end-to-end speech synthesis model uses both speaker embedding and noise representation as conditional inputs to model speaker and noise information respectively.  ...  It is worth investigating how to take advantage of low-quality and low resource voice data which can be easily obtained from the Internet for usage of synthesizing personalized voice.  ...  Noise representation condition To model the noise information, we use noise representation (Melspectrogram denoise masks, extracted from the speech enhancement model) as the conditional input of the decoder  ... 
arXiv:2005.12531v2 fatcat:unc2rvyw6rawve5qqapu2qhu4q

Classifier-adaptation knowledge distillation framework for relation extraction and event detection with imbalanced data

Dandan Song, Jing Xu, Jinhui Pang, Heyan Huang
2021 Information Sciences  
Fundamental information extraction tasks, such as relation extraction and event detection, suffer from a data imbalance problem.  ...  Like an instructor, the classifier improves the baseline model's ability to extract this sentence-level identification information from raw texts, thus benefiting overall performance.  ...  In the input layer, ordinary input embeddings include word embeddings, POS embeddings, and NER embeddings for relation extraction.  ... 
doi:10.1016/j.ins.2021.05.045 fatcat:6arhjpixqzd5pas7otq7rbjkuy

A Survey of Knowledge-Enhanced Text Generation [article]

Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, Meng Jiang
2022 arXiv   pre-print
To address this issue, researchers have considered incorporating various forms of knowledge beyond the input text into the generation models.  ...  Since 2014, various neural encoder-decoder models pioneered by Seq2Seq have been proposed to achieve the goal by learning to map input text to output text.  ...  One of the mainstream methods of constructing an internal KG is using open information extraction (OpenIE).  ... 
arXiv:2010.04389v3 fatcat:vzdtlz4j65g2va7gwkbmzyxkhq

Enhance the Word Vector with Prosodic Information for the Recurrent Neural Network Based TTS System

Xin Wang, Shinji Takaki, Junichi Yamagishi
2016 Interspeech 2016  
Experiment shows that using the enhanced word vectors as an input to the neural network-based acoustic model improves the accuracy of the predicted F0 trajectory.  ...  This paper presents a post-filtering approach to enhance the raw word vectors with prosodic information for the TTS task.  ...  Acknowledgements We thank the reviewers for the critical comments.  ... 
doi:10.21437/interspeech.2016-390 dblp:conf/interspeech/WangTY16 fatcat:wa3fmedhvzcyladz6l75pmzdhm

Enhanced Methodology for Relation Descriptor Extraction

K. Praveen Kumar
2014 International Journal of IT-based Management for Smart Business  
Relation extraction is an interesting filed in information extraction , in which predefined semantic relationships are identified from a text document.  ...  This method uses NNLM (natural neural learning model), morphology, grammar and semantic features for relation descriptor extraction.  ...  Word embeddings can be useful as input to an NLP model (mostly non-linear) or as additional features to enhance existing systems.  ... 
doi:10.21742/ijitmsb.2014.1.02 fatcat:mn237wvulvbszi3odf7p5uqb3e

Multi-Stream Semantics-Guided Dynamic Aggregation Graph Convolution Networks to Extract Overlapping Relations

XiuShan Liu, Jun Cheng, Qin Zhang
2021 IEEE Access  
The proposed model constructs the entity relation graphs by enumerating the possible candidates and external auxiliary information and adaptively manages the relevant substructure.  ...  INDEX TERMS Overlapping relation extraction, multiscale structural information, dynamic aggregation, long distance dependencies, refined graph, relevant substructure.  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their comments and helpful suggestions.  ... 
doi:10.1109/access.2021.3062231 fatcat:zu4rrzkalfcsxdol7x63lzhadu

An Entity Relation Extraction Method for Few-Shot Learning on the Food Health and Safety Domain

Min Zuo, Baoyu Zhang, Qingchuan Zhang, Wenjing Yan, Dongmei Ai, Xin Ning
2022 Computational Intelligence and Neuroscience  
This paper proposes an entity relation extraction method FHER for the few-shot learning in the food health and safety domain.  ...  The experimental results show that the method can effectively extract domain-related entities and their relations in a small sample size environment.  ...  For supervised deep learning models, small sample size can lead to an underfitting of the model. In other words, there is not enough information to train a valid model.  ... 
doi:10.1155/2022/1879483 pmid:35237307 pmcid:PMC8885244 fatcat:vxswpnbbw5ggdb2e6fbw6jx4ve

RECA: Relation Extraction Based on Cross-Attention Neural Network

Xiaofeng Huang, Zhiqiang Guo, Jialiang Zhang, Hui Cao, Jie Yang
2022 Electronics  
Extracting entities and relations, as a crucial part of many tasks in natural language processing, transforms the unstructured text information into structured information and provides corresponding data  ...  This work introduces a pre-trained BERT model and a dilated gated convolutional neural network (DGCNN) as an encoder to distinguish the long-range semantics representation from the input sequence.  ...  Related Works Extraction of relational triplets from unstructured sentences has always been a fundamental task for information extraction.  ... 
doi:10.3390/electronics11142161 fatcat:wcarjdx5pvaipk5bic654ee3du

An Analysis of Public Environment-Oriented Marxist Philosophy Content Dissemination

Jinming Guo, Haibo Hu, Fu-Sheng Tsai
2022 Journal of Environmental and Public Health  
and the advantages of the long-term recurrent convolutional network (LRCN) model in video content recognition, an attention mechanism-based LRCN model is proposed, which simulates the attention characteristics  ...  Because of the development of Internet technology, in order to ensure the validity of the uploaded videos related to Marxist philosophy on the platform, combining the research on human visual perception  ...  We-media has become an important way for people to exchange information and has a profound impact on information transmission in various fields [12, 13] .  ... 
doi:10.1155/2022/7873226 pmid:35692662 pmcid:PMC9187483 fatcat:ibbxdopnszdfdcugx6thpsj7xa

An Entity Relation Extraction Method Based on Dynamic Context and Multi-Feature Fusion

Xiaolin Ma, Kaiqi Wu, Hailan Kuang, Xinhua Liu
2022 Applied Sciences  
Dynamic context selector, a kind of mask idea, will divide the matrix into some regions, selecting the information of region as the input of model dynamically.  ...  It is noted that we also use Bi-LSTM_ATT to improve compatibility of longer text in feature extracting layer and enhance context information by combining with the tags of entity in feature fusion layer  ...  Informed Consent Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12031532 fatcat:yea4bfoa4raqbdrj77ch25vchm
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