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Learning to Bootstrap for Entity Set Expansion

Lingyong Yan, Xianpei Han, Le Sun, Ben He
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
Bootstrapping for Entity Set Expansion (ESE) aims at iteratively acquiring new instances of a specific target category.  ...  feedback for pattern evaluation and adaptively score entities given sparse supervision signals.  ...  edge, (b) The Monte Carlo Tree Search for the pattern evaluation in a bootstrapping system for entity set expansion.  ... 
doi:10.18653/v1/d19-1028 dblp:conf/emnlp/YanHSH19 fatcat:yhb3i7kylretfaz65bcvxukhia

Progressive Adversarial Learning for Bootstrapping: A Case Study on Entity Set Expansion [article]

Lingyong Yan, Xianpei Han, Le Sun
2021 arXiv   pre-print
Bootstrapping has become the mainstream method for entity set expansion.  ...  Specifically, the expansion boundaries of different bootstrapping iterations are learned via different discriminator networks; the bootstrapping network is the generator to generate new positive entities  ...  Introduction Bootstrapping is a fundamental technique for entity set expansion (ESE).  ... 
arXiv:2109.12082v1 fatcat:inuocx3sqrfkddv3lmtwv4jmuq

End-to-End Bootstrapping Neural Network for Entity Set Expansion

Lingyong Yan, Xianpei Han, Ben He, Le Sun
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Bootstrapping for entity set expansion (ESE) has long been modeled as a multi-step pipelined process.  ...  problem; 2) it is hard to exploit the high-order entity-pattern relations for entity set expansion.  ...  Second, it is hard to exploit the high-order entity-pattern relations for entity set expansion.  ... 
doi:10.1609/aaai.v34i05.6482 fatcat:5traskqpq5ev5m4ndrjngivhwq

Bilingual Product Name Dictionary Construction Using a Two Stage Method

Yatian Shen, Xuanjing Huang
2014 Proceedings of The Third CIPS-SIGHAN Joint Conference on Chinese Language Processing  
the problem about expansion of entity set in a monolingual language, but the expansion of bilingual entity is really blank problem from comparable corpora.  ...  A typical example is to use/Honda-X"as seed entity, and derive other entities(e.g.,/Ford-4A") in the same concept set of product name.  ...  Bootstrapping for Entity Set Expansion In this paper, we expand seed entity set into a more complete set by discovering other entities that also belong to the same concept set.  ... 
doi:10.3115/v1/w14-6810 dblp:conf/acl-sighan/ShenH14 fatcat:divwtljglfad5mbvt6yrb3yruy

LearnIt: On-Demand Rapid Customization for Event-Event Relation Extraction

Bonan Min, Manaj Srivastava, Haoling Qiu, Prasannakumar Muthukumar, Joshua Fasching
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Experiments show that it enables users to create extractors for 6 types of causal and temporal relations, with less than 20 minutes of effort per type.  ...  The system provides a suite of algorithms, flexible workflows, and a user interface (UI), to allow rapid customization of event-event relation extractors for new types and domains of interest.  ...  Workflow 2: Pattern/pair set expansion: This workflow incorporates ideas from distributional-similarity-based paraphrase and entity set expansion.  ... 
doi:10.1609/aaai.v34i09.7102 fatcat:udwag5cvyrdtnizt2t6xsyq4he

Distributed Representations of Words to Guide Bootstrapped Entity Classifiers

Sonal Gupta, Christopher D. Manning
2015 Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies  
We use the word vectors to expand entity sets used for training classifiers in a bootstrapped pattern-based entity extraction system.  ...  The results suggest that distributed representations can provide good directions for generalization in a bootstrapping system.  ...  Cautious approaches have been shown to be better for bootstrapped learning (Abney, 2004) . 4 We tried expanding just the positive entities and just the negative entities.  ... 
doi:10.3115/v1/n15-1128 dblp:conf/naacl/GuptaM15 fatcat:7jkcj75wdfbarctrits5qano7a

Contrastive Learning with Hard Negative Entities for Entity Set Expansion [article]

Yinghui Li, Yangning Li, Yuxin He, Tianyu Yu, Ying Shen, Hai-Tao Zheng
2022 arXiv   pre-print
Entity Set Expansion (ESE) is a promising task which aims to expand entities of the target semantic class described by a small seed entity set.  ...  To address this challenge, we devise an entity-level masked language model with contrastive learning to refine the representation of entities.  ...  To do this, we firstly generate positive/negative entities for each semantic class from seed sets and previous expansion results.  ... 
arXiv:2204.07789v2 fatcat:dyeoq2352vgdtnup5q4znpxj74

Bootstrapping Named Entity Recognition in E-Commerce with Positive Unlabeled Learning [article]

Hanchu Zhang, Leonhard Hennig, Christoph Alt, Changjian Hu, Yao Meng, Chao Wang
2020 arXiv   pre-print
To address this problem, we present a bootstrapped positive-unlabeled learning algorithm that integrates domain-specific linguistic features to quickly and efficiently expand the seed dictionary.  ...  Named Entity Recognition (NER) in domains like e-commerce is an understudied problem due to the lack of annotated datasets.  ...  Acknowledgments We would like to thank the reviewers for their valuable comments and feedback.  ... 
arXiv:2005.11075v1 fatcat:dchlo2s5jzdkdcc4uqa3odayii

Lightly supervised acquisition of named entities and linguistic patterns for multilingual text mining

César de Pablo-Sánchez, Isabel Segura-Bedmar, Paloma Martínez, Ana Iglesias-Maqueda
2012 Knowledge and Information Systems  
for intelligent applications for helping to access information.  ...  Keywords Named entity recognition and categorization · Information extraction · Multilingual natural language processing · Bootstrapping algorithms Introduction Nowadays there exists an increasing need  ...  Pattern expansion In this phase, a new set of entity instances are used to acquire new candidate patterns.  ... 
doi:10.1007/s10115-012-0502-0 fatcat:ukfcua2ru5cfbicckj4hwgv5my

A novel lexicalized HMM-based learning framework for web opinion mining

Wei Jin, Hung Hay Ho
2009 Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09  
This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product.  ...  Opinion expressions and sentences are also identified and opinion orientations for each recognized product entity are classified as positive or negative.  ...  The bootstrap document set (containing 1435 documents for 10 cameras) was used by the bootstrapping process to extract high confidence data through self-learning (newly discovered high confidence data  ... 
doi:10.1145/1553374.1553435 dblp:conf/icml/JinH09 fatcat:dqurdryjkjajrgaqvpyxyjqda4

OpinionMiner

Wei Jin, Hung Hay Ho, Rohini K. Srihari
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
This makes it difficult for a potential customer to read them to make an informed decision.  ...  Opinion expressions are identified and opinion orientations for each recognized product entity are classified as positive or negative.  ...  The bootstrap document set (containing 1435 documents for 10 cameras) was used by the bootstrapping process to extract high confidence data through self-learning (newly discovered high confidence data  ... 
doi:10.1145/1557019.1557148 dblp:conf/kdd/JinHS09 fatcat:46w7z3g3z5fdjcz3fj6zckt4di

Entity Set Expansion based on Bootstrapping Methods using Topic Information
トピック情報を用いたブートストラップ法に基づく語彙獲得

Kugatsu Sadamitsu, Kuniko Saito, Kenji Imamura, Yoshihiro Matsuo, Genichiro Kikui
2012 Journal of Natural Language Processing  
"Learning to probabilistically identify authoritative documents."  ...  In Proceedings of the Advances in Neural Information Processing Systems Workshop on Machine Learning for Web Search. Blei, D. M., Ng, A. Y., and Jordan, M. I. (2003). "Latent dirichlet allocation."  ... 
doi:10.5715/jnlp.19.89 fatcat:bogmvabkxratlakbnv34ezlppq

TSE-NER: An Iterative Approach for Long-Tail Entity Extraction in Scientific Publications [chapter]

Sepideh Mesbah, Christoph Lofi, Manuel Valle Torre, Alessandro Bozzon, Geert-Jan Houben
2018 Lecture Notes in Computer Science  
We introduce different strategies for training data extraction, semantic expansion, and result entity filtering.  ...  This paper presents an iterative approach for training NER and NET classifiers in scientific publications that relies on minimal human input, namely a small seed set of instances for the targeted entity  ...  The same holds for rulebased techniques, which rely on formal languages to express rules and require comprehensive domain knowledge and time to create. Bootstrapping and Entity Set Expansion.  ... 
doi:10.1007/978-3-030-00671-6_8 fatcat:bzaybmrb6jbancylfi66okppbm

A Lightweight Front-end Tool for Interactive Entity Population [article]

Hidekazu Oiwa, Yoshihiko Suhara, Jiyu Komiya, Andrei Lopatenko
2017 arXiv   pre-print
Moreover, an entity expansion module is implemented as external APIs. This design makes it easy to continuously improve interactive entity population pipelines.  ...  We implement key components necessary for effective interactive entity population: 1) GUI-based dashboards to quickly modify an entity dictionary, and 2) entity highlighting on documents for quickly viewing  ...  A major approach to entity population is bootstrapping, which uses several entities that have been prepared as a seed set for finding new entities.  ... 
arXiv:1708.00481v1 fatcat:4t2lc3bw3rgubg2jzavt7cyjai

Entity set expansion in opinion documents

Lei Zhang, Bing Liu
2011 Proceedings of the 22nd ACM conference on Hypertext and hypermedia - HT '11  
The system has to find the rest from a corpus. This implies that the discovered entities must be of the same type/class. This is the set expansion problem.  ...  Additionally, like any learning algorithm, Bayesian Sets requires the user to engineer a set of features.  ...  [18] adopts a machine learning approach called positive and unlabeled learning (PU learning) to model set expansion problem.  ... 
doi:10.1145/1995966.1996002 dblp:conf/ht/ZhangL11 fatcat:y7br2ycrwzegdpkmwipqr5epru
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