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检索条件"任意字段=5th Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs 2010"
16 条 记 录,以下是1-10 订阅
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Reducing Knowledge Noise for Improved Semantic Analysis in Biomedical natural language processing Applications  5
Reducing Knowledge Noise for Improved Semantic Analysis in B...
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5th workshop on Clinical natural language processing, ClinicalNLP 2023. held at ACL 2023
作者: Naseem, Usman thapa, Surendrabikram Zhang, Qi Hu, Liang Masood, Anum Nasim, Mehwish University of Sydney Australia Virginia Tech United States Tongji University China DeepBlue Academy of Sciences China Norwegian University of Science and Technology Norway University of Western Australia Australia Flinders University Australia
graph-based techniques have gained traction for representing and analyzing data in various natural language processing (NLP) tasks. Knowledge graph-based language representation models have shown promising results in ... 详细信息
来源: 评论
Sharing Parameter by Conjugation for Knowledge graph Embeddings in Complex Space  16
Sharing Parameter by Conjugation for Knowledge Graph Embeddi...
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16th workshop on graph-based methods for natural language processing, textgraphs 2022, in conjunction with the 29th International Conference on Computational Linguistics, COLING 2022
作者: Feng, Xincan Qu, Zhi Cheng, Yuchang Watanabe, Taro Yugami, Nobuhiro Natural Language Processing Laboratory Nara Institute of Science and Technology Japan Multilingual Knowledge Computing Laboratory Fujitsu Ltd Japan
A Knowledge graph (KG) is the directed graphical representation of entities and relations in the real world. KG can be applied in diverse natural language processing (NLP) tasks where knowledge is required. the need t... 详细信息
来源: 评论
Speech Emotion Classification based on Dynamic graph Attention Network
Speech Emotion Classification Based on Dynamic Graph Attenti...
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Electronic Communication and Artificial Intelligence (IWECAI), International workshop on
作者: Xu Shi Xianhua Dai School of Electronics and Information Technology Sun Yat-sen University Guangzhou P.R.China School of Cyber Science and Technology Sun Yat-sen University Shenzhen P.R.China
With the development of artificial intelligence and natural language processing, speech emotion analysis technology has gradually gained widespread attention as an important research field. the complexity of speech em... 详细信息
来源: 评论
A graph based semi-supervised approach for analysis of derivational nouns in Sanskrit  11
A graph based semi-supervised approach for analysis of deriv...
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11th workshop on graph-based methods for natural language processing, textgraphs 2017, in conjunction with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
作者: Krishna, Amrith Satuluri, Pavankumar Ponnada, Harshavardhan Ahmed, Muneeb Arora, Gulab Hiware, Kaustubh Goyal, Pawan School of Linguistics and Literary Studies Chinmaya Vishwavidyapeeth CEG Campus India Dept. of Electrical Engineering Indian Institute of Technology BHU India Dept. of Computer Science and Engineering Indian Institute of Technology Kharagpur India
Derivational nouns are widely used in Sanskrit corpora and is a prevalent means of productivity in the language. Currently there exists no analyser that identifies the derivational nouns. We propose a semi supervised ... 详细信息
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graph-based semi-supervised learning for natural language understanding  13
Graph-based semi-supervised learning for natural language un...
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13th workshop on graph-based methods for natural language processing, textgraphs 2019, in conjunction with the 2019 Conference on Empirical methods in natural language processing and 9th International Joint Conference on natural language processing, EMNLP-IJCNLP 2019
作者: Qiu, Zimeng Cho, Eunah Ma, Xiaochun Campbell, William M. Electrical and Computer Engineering Department Carnegie Mellon University United States Amazon Alexa AI
Semi-supervised learning is an efficient method to augment training data automatically from unlabeled data. Development of many natural language understanding (NLU) applications has a challenge where unlabeled data is... 详细信息
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Deep learning with language models improves named entity recognition for PharmaCoNER
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BMC BIOINFORMATICS 2021年 第SUPPL 1期22卷 602-602页
作者: Sun, Cong Yang, Zhihao Wang, Lei Zhang, Yin Lin, Hongfei Wang, Jian Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China Beijing Inst Hlth Adm & Med Informat Beijing Peoples R China
Background the recognition of pharmacological substances, compounds and proteins is essential for biomedical relation extraction, knowledge graph construction, drug discovery, as well as medical question answering. Al... 详细信息
来源: 评论
UNIMIB@NEEL-IT : Named entity recognition and linking of Italian tweets  3
UNIMIB@NEEL-IT : Named entity recognition and linking of Ita...
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3rd Italian Conference on Computational Linguistics, CLiC-it 2016 and 5th Evaluation Campaign of natural language processing and Speech Tools for Italian, EVALITA 2016
作者: Cecchini, Flavio Massimiliano Fersini, Elisabetta Manchanda, Pikakshi Messina, Enza Nozza, Debora Palmonari, Matteo Sas, Cezar University of Milano BicoccaMilan Italy
this paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian tweets (NEEL-IT). the proposed pipeline, which represents an entry level system, is compos... 详细信息
来源: 评论
Understanding seed selection in bootstrapping  8
Understanding seed selection in bootstrapping
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8th workshop on graph-based methods for natural language processing, textgraphs 2013, at the Conference on Empirical methods in natural language processing, EMNLP 2013
作者: Ehara, Yo Sato, Issei Oiwa, Hidekazu Nakagawa, Hiroshi Graduate School of Information Science and Technology United States Information Technology Center University of Tokyo / 7-3-1 Hongo Bunkyo-ku Tokyo Japan JSPS Research Fellow Kojimachi Business Center Building 5-3-1 Kojimachi Chiyoda-ku Tokyo Japan
Bootstrapping has recently become the focus of much attention in natural language processing to reduce labeling cost. In bootstrapping, unlabeled instances can be harvested from the initial labeled "seed" se... 详细信息
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textgraphs 2010 - 2010 workshop on graph-based methods for natural language processing at the 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 - Proceedings of the workshop
TextGraphs 2010 - 2010 Workshop on Graph-Based Methods for N...
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2010 workshop on graph-based methods for natural language processing, textgraphs 2010 at the 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 - Proceedings of the workshop
the proceedings contain 16 papers. the topics discussed include: graph-based clustering for computational linguistics: a survey;towards the automatic creation of a wordnet from a term-based lexical network;an investig... 详细信息
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Word sense induction by community detection
Word sense induction by community detection
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6th workshop on graph-based methods for natural language processing, textgraphs 2011
作者: Jurgens, David HRL Laboratories LLC Malibu CA United States Department of Computer Science Malibu University of California Los Angeles United States
Word Sense Induction (WSI) is an unsupervised approach for learning the multiple senses of a word. graph-based approaches to WSI frequently represent word co-occurrence as a graph and use the statistical properties of... 详细信息
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