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How Knowledge Graph and Attention Help? A Quantitative Analysis into Bag-level Relation Extraction [article]

Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua
2021 arXiv   pre-print
In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).  ...  However, only qualitative analysis and ablation study are provided as evidence.  ...  This work is partially supported by A*STAR through the Industry Alignment Fund -Industry Collaboration Projects Grant, by NTU (NTU-ACE2020-01) and Ministry of Education (RG96/20), and by the National Research  ... 
arXiv:2107.12064v1 fatcat:b5r7ft5ryjb2xgusih3cdvjasu

How Knowledge Graph and Attention Help? A Qualitative Analysis into Bag-level Relation Extraction

Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua
2021 Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)   unpublished
In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).  ...  However, only qualitative analysis and ablation study are provided as evidence.  ...  This work is partially supported by A*STAR through the Industry Alignment Fund -Industry Collaboration Projects Grant, by NTU (NTU-ACE2020-01) and Ministry of Education (RG96/20), and by the National Research  ... 
doi:10.18653/v1/2021.acl-long.359 fatcat:xjzspjlzfbg65e4rcj6t5ag3dq

Does deep learning help topic extraction? A kernel k-means clustering method with word embedding

Yi Zhang, Jie Lu, Feng Liu, Qian Liu, Alan Porter, Hongshu Chen, Guangquan Zhang
2018 Journal of Informetrics  
Additionally, this empirical analysis reveals insights into both overlapping and diverse research interests among the three journals that would benefit journal publishers, editorial boards, and research  ...  An empirical study on bibliometric topic extraction from articles published by three top-tier bibliometric journals between 2000 and 2017, supported by expert knowledge-based evaluations, provides supplemental  ...  Acknowledgements We acknowledge Arho Suominen and Ying Huang for their efforts in the pre-round expert knowledge-based evaluation, and our heartfelt appreciation goes to Lutz Bornmann, Kevin Boyack, Andrea  ... 
doi:10.1016/j.joi.2018.09.004 fatcat:t75tldepafcxrptzk5s2jc26ki

Predicting the Helpfulness Score of Product Reviews Using an Evidential Score Fusion Method

Fatemeh Fouladfar, Mohammad Naderi Dehkordi, Mohammad Ehsan Basiri
2020 IEEE Access  
This article presents a new model for specifying the usefulness of comments using the textual features extracted from the reviews.  ...  Various types of features including emotion-related, linguistic and text-related features, valence, arousal, and dominance (VAD) values, review-length and polarity of comments are exploited in this study  ...  of VAD and text-related features have better helpfulness recognition ability.  ... 
doi:10.1109/access.2020.2988872 fatcat:4wernhazpnbmnomiiahgzebfhu

An Empirical Study of Corpus-Based Response Automation Methods for an E-mail-Based Help-Desk Domain

Yuval Marom, Ingrid Zukerman
2009 Computational Linguistics  
Related work is discussed in Section 8, and concluding remarks are presented in Section 9.  ...  Sentence-level methods correspond to applying extractive multi-document summarization techniques to collate units of information from more than one e-mail.  ...  The authors also thank Hewlett-Packard for the extensive anonymized help-desk data, Nathalie Japkowicz for her advice on the meta-learning portions of this work, and the anonymous reviewers for their insightful  ... 
doi:10.1162/coli.2009.35.4.35404 fatcat:qdzvrmu42nffhl5rlpf44rexg4

Graph Neural Networks with Generated Parameters for Relation Extraction

Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-Seng Chua, Maosong Sun
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
We verify GP-GNNs in relation extraction from text, both on bag-and instancesettings.  ...  We also perform a qualitative analysis to demonstrate that our model could discover more accurate relations by multi-hop relational reasoning.  ...  This work 10 http://thunlp.org is jointly supported by the NSFC project under the grant No. 61661146007 and the NExT++ project, the National Research Foundation, Prime Ministers Office, Singapore under  ... 
doi:10.18653/v1/p19-1128 dblp:conf/acl/ZhuLLFCS19 fatcat:eytul56vnbdhff2ugwvjadccpe

Graph Neural Networks with Generated Parameters for Relation Extraction [article]

Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua, Maosong Sun
2019 arXiv   pre-print
We also perform a qualitative analysis to demonstrate that our model could discover more accurate relations by multi-hop relational reasoning.  ...  We verify GP-GNNs in relation extraction from text.  ...  we will show that our models could also help enhance the performance of bag-level relation extraction on a distantly labeled test set 4 , and (iii) we also split a subset of distantly labeled test set,  ... 
arXiv:1902.00756v1 fatcat:lpnbujhf4nd5hdu7iltiif7jwu

Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision [article]

Yang Li, Guodong Long, Tao Shen, Jing Jiang
2021 arXiv   pre-print
Distant supervision uses triple facts in knowledge graphs to label a corpus for relation extraction, leading to wrong labeling and long-tail problems.  ...  It consists of (1) a pairwise type-enriched sentence encoding module injecting both context-free and -related backgrounds to alleviate sentence-level wrong labeling, and (2) a hierarchical type-sentence  ...  Inspired by self-attentive sentence encoding ), we present a bag-level type-attentive module, which compresses C into a single vector representation to facilitate type-enriching.  ... 
arXiv:2109.09036v1 fatcat:h2dsow3xebgpfgmhgawdrbj5he

Enriching semantic knowledge bases for opinion mining in big data applications

A. Weichselbraun, S. Gindl, A. Scharl
2014 Knowledge-Based Systems  
This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications  ...  Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process.  ...  ERA-NET, and the COMET Project (www.htwchur.ch/ comet), funded by the Swiss Commission for Technology and Innovation (CTI).  ... 
doi:10.1016/j.knosys.2014.04.039 pmid:25431524 pmcid:PMC4235782 fatcat:k7rcec6qeja6rkkjuou7z7g6si

Semantic Relations and Deep Learning [article]

Vivi Nastase, Stan Szpakowicz
2021 arXiv   pre-print
A new Chapter 5 of the book, by Vivi Nastase and Stan Szpakowicz, discusses relation classification/extraction in the deep-learning paradigm which arose after the first edition appeared.  ...  The second edition of "Semantic Relations Between Nominals" by Vivi Nastase, Stan Szpakowicz, Preslav Nakov and Diarmuid \'O S\'eaghdha has been published in April 2021 by Morgan & Claypool (www.morganclaypoolpublishers.com  ...  Bags which share a relation label are assembled into a bag group. An attention mechanism helps weight sentences for the construction of the bag representation.  ... 
arXiv:2009.05426v4 fatcat:rmzoalfwcza4nex7pd4u6w7kbe

Leveraging Domain Context for Question Answering Over Knowledge Graph

Peihao Tong, Qifan Zhang, Junjie Yao
2019 Data Science and Engineering  
., meta-paths within the targeting knowledge graph. On top of these, we design a cross-attention mechanism to improve the question and answer matching performance.  ...  With the growing availability of different knowledge graphs in a variety of domains, question answering over knowledge graph (KG-QA) becomes a prevalent information retrieval approach.  ...  reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s41019-019-00109-w fatcat:eqymus5u2jg5pkllu6kldi3gk4

Discriminative Latent Semantic Graph for Video Captioning [article]

Yang Bai, Junyan Wang, Yang Long, Bingzhang Hu, Yang Song, Maurice Pagnucco, Yu Guan
2021 arXiv   pre-print
information into latent object proposal. 2) Visual Knowledge: Latent Proposal Aggregation is proposed to dynamically extract visual words with higher semantic levels. 3) Sentence Validation: A novel Discriminative  ...  Our main contribution is to identify three key problems in a joint framework for future video summarization tasks. 1) Enhanced Object Proposal: we propose a novel Conditional Graph that can fuse spatio-temporal  ...  Second, how to extract visual knowledge from enhanced object proposals shares the same spirit of the traditional Bag-of-Visual-Words (BoVW) paradigm.  ... 
arXiv:2108.03662v1 fatcat:6okzuqntjngcvl7cndxybjnjje

Combining Distant and Direct Supervision for Neural Relation Extraction [article]

Iz Beltagy, Kyle Lo, Waleed Ammar
2019 arXiv   pre-print
In relation extraction with distant supervision, noisy labels make it difficult to train quality models.  ...  Previous neural models addressed this problem using an attention mechanism that attends to sentences that are likely to express the relations.  ...  supervision approach of relation extraction, where a knowledge base (KB) and a text corpus are used to automatically generate a large dataset of labeled bags of sentences (a set of sentences that might  ... 
arXiv:1810.12956v2 fatcat:c6uggneh2zajxjlmp62e72nj4m

Combining Distant and Direct Supervision for Neural Relation Extraction

Iz Beltagy, Kyle Lo, Waleed Ammar
2019 Proceedings of the 2019 Conference of the North  
In relation extraction with distant supervision, noisy labels make it difficult to train quality models.  ...  Previous neural models addressed this problem using an attention mechanism that attends to sentences that are likely to express the relations.  ...  supervision approach of relation extraction, where a knowledge base (KB) and a text corpus are used to automatically generate a large dataset of labeled bags of sentences (a set of sentences that might  ... 
doi:10.18653/v1/n19-1184 dblp:conf/naacl/BeltagyLA19 fatcat:xfnyer4tojcmhgf4zp3tutnhdm

A Survey on Graph-Based Deep Learning for Computational Histopathology [article]

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 arXiv   pre-print
As such, graph data representations and deep learning have attracted significant attention for encoding tissue representations, and capturing intra- and inter- entity level interactions.  ...  In this review, we provide a conceptual grounding for graph analytics in digital pathology, including entity-graph construction and graph architectures, and present their current success for tumor localization  ...  extraction and selection is conducted followed by a bag-level classification.  ... 
arXiv:2107.00272v2 fatcat:3eskkeref5ccniqsjgo3hqv2sa
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