Ensemble Learning of Named Entity Recognition Algorithms using Multilayer Perceptron for the Multilingual Web of Data

被引：3

作者：

Speck, Rene ^{[1
]}

Ngomo, Axel-Cyrille Ngonga ^{[2
]}

机构：

[1] Univ Leipzig, Data Sci Grp, Augustuspl 10, D-04109 Leipzig, Germany

[2] Univ Paderborn, Data Sci Grp, Pohlweg 51, D-33098 Paderborn, Germany

来源：

K-CAP 2017: PROCEEDINGS OF THE KNOWLEDGE CAPTURE CONFERENCE | 2017年

基金：

欧盟地平线“2020”;

关键词：

Named Entity Recognition; Ensemble Learning; Multilingual; Semantic Web;

D O I：

10.1145/3148011.3154471

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Implementing the multilingual Semantic Web vision requires transforming unstructured data in multiple languages from the Document Web into structured data for the multilingual Web of Data. We present the multilingual version of FOX, a knowledge extraction suite which supports this migration by providing named entity recognition based on ensemble learning for five languages. Our evaluation results show that our approach goes beyond the performance of existing named entity recognition systems on all five languages. In our best run, we outperform the state of the art by a gain of 32.38% F1-Score points on a Dutch dataset. More information and a demo can be found at http://fox.aksw.org as well as an extended version of the paper(1) descriping the evaluation in detail.

引用

页数：4

共 50 条

[21] Named Entity Recognition for Amharic Using Deep Learning
Gamback, Bjorn
Sikdar, Utpal Kumar
2017 IST-AFRICA WEEK CONFERENCE (IST-AFRICA), 2017,
[22] Nested Named Entity Recognition Using Multilayer Recurrent Neural Networks
Truong-Son Nguyen
Le-Minh Nguyen
COMPUTATIONAL LINGUISTICS, PACLING 2017, 2018, 781 : 233 - 246
[23] Named entity recognition and classification in biomedical text using classifier ensemble
Saha, Sriparna
Ekbal, Asif
Sikdar, Utpal Kumar
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, 2015, 11 (04) : 365 - 391
[24] Learning Multilingual Meta-Embeddings for Code-Switching Named Entity Recognition
Winata, Genta Indra
Lin, Zhaojiang
Fung, Pascale
4TH WORKSHOP ON REPRESENTATION LEARNING FOR NLP (REPL4NLP-2019), 2019, : 181 - 186
[25] Tuning Multilingual Transformers for Named Entity Recognition on Slavic Languages
Arkhipov, Mikhail
Trofimova, Maria
Kuratov, Yuri
Sorokin, Alexey
7TH WORKSHOP ON BALTO-SLAVIC NATURAL LANGUAGE PROCESSING (BSNLP'2019), 2019, : 89 - 93
[26] On the Strength of Character Language Models for Multilingual Named Entity Recognition
Yu, Xiaodong
Mayhew, Stephen
Sammons, Mark
Roth, Dan
2018 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2018), 2018, : 3073 - 3077
[27] Named entity recognition for Web content filtering
Hidalgo, JMG
García, FC
Sanz, EP
NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, PROCEEDINGS, 2005, 3513 : 286 - 297
[28] Ranking algorithms for named-entity extraction: Boosting and the voted perceptron
Collins, M
40TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE, 2002, : 489 - 496
[29] Ensemble based Active Annotation for Named Entity Recognition
Ekbal, Asif
Saha, Sriparna
Singh, Dhirendra
2012 THIRD INTERNATIONAL CONFERENCE ON EMERGING APPLICATIONS OF INFORMATION TECHNOLOGY (EAIT), 2012, : 331 - 334
[30] Continual Learning for Named Entity Recognition
Monaikul, Natawut
Castellucci, Giuseppe
Filice, Simone
Rokhlenko, Oleg
THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 13570 - 13577

← 1 2 3 4 5 →