Journal of Frontiers of Computer Science and Technology ›› 2022, Vol. 16 ›› Issue (11): 2565-2574.DOI: 10.3778/j.issn.1673-9418.2103027
• Artificial Intelligence • Previous Articles Next Articles
ZHOU Qi, TAO Wan+(), KONG Chao, CUI Baiting
Received:
2021-03-26
Revised:
2021-05-14
Online:
2022-11-01
Published:
2021-05-18
About author:
ZHOU Qi, born in 1997, M.S. candidate. Her research interests include cloud computing and big data processing.Supported by:
通讯作者:
+ E-mail: taowan@ahpu.edu.cn作者简介:
周祺(1997—),女,安徽宿州人,硕士研究生,主要研究方向为云计算、大数据处理。基金资助:
CLC Number:
ZHOU Qi, TAO Wan, KONG Chao, CUI Baiting. Fine-Grained Entity Classification Method Fused with Memory Network[J]. Journal of Frontiers of Computer Science and Technology, 2022, 16(11): 2565-2574.
周祺, 陶皖, 孔超, 崔佰婷. 融合记忆网络的细粒度实体分类方法[J]. 计算机科学与探索, 2022, 16(11): 2565-2574.
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URL: http://fcst.ceaj.org/EN/10.3778/j.issn.1673-9418.2103027
统计指标 | FIGER | BBN |
---|---|---|
类型数 | 113 | 47 |
最深层次 | 2 | 2 |
mentions-训练 | 2 009 898 | 86 078 |
mentions-测试 | 563 | 12 845 |
干净mentions-训练/% | 64.46 | 75.92 |
干净mentions-测试/% | 88.28 | 100.00 |
Table 1 Statistics in datasets
统计指标 | FIGER | BBN |
---|---|---|
类型数 | 113 | 47 |
最深层次 | 2 | 2 |
mentions-训练 | 2 009 898 | 86 078 |
mentions-测试 | 563 | 12 845 |
干净mentions-训练/% | 64.46 | 75.92 |
干净mentions-测试/% | 88.28 | 100.00 |
超参数 | FIGER | BBN |
---|---|---|
256 | 256 | |
0.002 | 0.007 | |
250 | 250 | |
500 | 500 | |
500 | 500 | |
1 | 1 | |
0.4 | 0.4 | |
0.000 1 | 0.000 2 |
Table 2 Hyperparameter setting
超参数 | FIGER | BBN |
---|---|---|
256 | 256 | |
0.002 | 0.007 | |
250 | 250 | |
500 | 500 | |
500 | 500 | |
1 | 1 | |
0.4 | 0.4 | |
0.000 1 | 0.000 2 |
[1] | 冯建周, 马祥聪. 基于迁移学习的细粒度实体分类方法的研究[J]. 自动化学报, 2020, 46(8): 1759-1766. |
FENG J Z, MA X C. Research on fine-grained entity classi-fication method based on transfer learning[J]. Acta Auto-matica Sinica, 2020, 46(8): 1759-1766. | |
[2] | LEE C, HWANG Y G, OH H J, et al. Fine-grained named entity recognition using conditional random fields for ques-tion answering[C]// LNCS 4182: Proceedings of the 3rd Asia Information Retrieval Symposium Information Retri-eval Technology, Singapore, Oct 16-18, 2006. Berlin, Heid-elberg: Springer, 2006: 581-587. |
[3] | SEKINE S. Extended named entity ontology with attribute information[C]// Proceedings of the 2008 International Con-ference on Language Resources and Evaluation, Marrak-ech, May 26-Jun 1, 2008: 1-6. |
[4] | LING X, WELD D S. Fine-grained entity recognition[C]// Proceedings of the 26th AAAI Conference on Artificial Intelligence, Toronto, Jul 22-26, 2012. Menlo Park: AAAI, 2012: 94-100. |
[5] | MINTZ M, BILLS S, SNOW R, et al. Distant supervision for relation extraction without labeled data[C]// Proceedings of the 47th Annual Meeting of the Association for Comput-ational Linguistics and the 4th International Joint Confer-ence on Natural Language Processing of the AFNLP, Sing-apore, Aug 2-7, 2009. Stroudsburg: ACL, 2009: 1003-1011. |
[6] | YOSEF M A, BAUER S, HOFFART J, et al. HYENA: hie-rarchical type classification for entity names[C]// Proceed-ings of the 24th International Conference on Computat-ional Linguistics, Mumbai, Dec 8-15, 2012. India: Indian Institute of Technology Bombay, 2012: 1361-1370. |
[7] | YOGATAMA D, GILLICK D, LAZIC N. Embedding meth-ods for fine grained entity type classification[C]// Proceed-ings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, Beijing, Jul 26-31, 2015. Stroudsburg: ACL, 2015: 291-296. |
[8] | DONG X, GABRILOVICH E, HEITZ G, et al. Knowledge vault: a web-scale approach to probabilistic knowledge fusi-on[C]// Proceedings of the 20th ACM SIGKDD Internat-ional Conference on Knowledge Discovery and Data Mining, New York, Aug 24-27, 2014. New York: ACM, 2014: 601-610. |
[9] | DEL CORRO L, ABUJABAL A, GEMULLA R, et al. FINET: context-aware fine-grained named entity typing[C]// Proce-edings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Sep 17-21, 2015. Str-oudsburg: ACL, 2015: 868-878. |
[10] | SHIMAOKA S, STENETORP P, INUI K, et al. An atten-tive neural architecture for fine-grained entity type classi-fication[C]// Proceedings of the 5th Workshop on Auto-mated Knowledge Base Construction, San Diego, Jun 17, 2016. Stroudsburg: ACL, 2016: 69-74. |
[11] |
马建红, 张炳斐, 张少光, 等. 基于主动MCNN-SCRF的新能源汽车命名实体识别[J]. 计算机工程与应用, 2019, 55(7): 23-29.
DOI |
MA J H, ZHANG B F, ZHANG S G, et al. New energy vehicle named entity recognition based on active MCNN-SCRF[J]. Computer Engineering and Applications, 2019, 55(7): 23-29. | |
[12] | 盛剑, 向政鹏, 秦兵, 等. 多场景文本的细粒度命名实体识别[J]. 中文信息学报, 2019, 33(6): 80-87. |
SHENG J, XIANG Z P, QIN B, et al. Fine-grained named entity recognition for multi-scene text[J]. Journal of Chinese Information Processing, 2019, 33(6): 80-87. | |
[13] |
王红, 林海舟, 卢林燕. 基于Att_GCN模型的知识图谱推理算法[J]. 计算机工程与应用, 2020, 56(9): 183-189.
DOI |
WANG H, LIN H Z, LU L Y. Knowledge graph inference algorithm based on Att_GCN model[J]. Computer Engine-ering and Applications, 2020, 56(9): 183-189. | |
[14] | 胡新棒, 于溆乔, 李邵梅, 等. 基于知识增强的中文命名实体识别[J]. 计算机工程, 2021, 47(11): 84-92. |
HU X B, YU G Q, LI S M, et al. Chinese named entity recognition based on knowledge enhancement[J]. Computer Engineering, 2021, 47(11): 84-92. | |
[15] | 西尔艾力·色提, 艾山·吾买尔, 王路路, 等. 结合单词-字符引导注意力网络的中文旅游文本命名实体识别[J]. 计算机工程, 2021, 47(2): 39-45. |
XIERAILI S, AISHAN W, WANG L L, et al. Named entity recognition in Chinese tourism text based on wordcharacter guided attention network[J]. Computer Engineering, 2021, 47(2): 39-45. | |
[16] | LAWRENCE N D, SCHÖLKOPF B. Estimating a kernel Fisher discriminant in the presence of label noise[C]// Proceedings of the 18th International Conference on Mach-ine Learning, Williamstown, Jun 28-Jul 1, 2001. San Franci-sco: Morgan Kaufmann, 2001: 306-313. |
[17] | GILLICK D, LAZIC N, GANCHEV K, et al. Context-dependent fine-grained entity type tagging[J]. arXiv:1412.1820, 2014. |
[18] | REN X, HE W, QU M, et al. AFET: automatic fine-grained entity typing by hierarchical partial-label embedding[C]// Pro-ceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Nov 1-4, 2016. Strou-dsburg: ACL, 2016: 1369-1378. |
[19] | ABHISHEK A, ANAND A, AWEKAR A. Fine-grained entity type classification by jointly learning representations and label embeddings[C]// Proceedings of the 15th Conference of the European Chapter of the Association for Comput-ational Linguistics, Valencia, Apr 3-7, 2017. Stroudsburg: ACL, 2017: 797-807. |
[20] | XU P, BARBOSA D. Neural fine-grained entity type classi-fication with hierarchy-aware loss[C]// Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics:Human Langu-age Technologies, New Orleans, Jun 1-6, 2018. Stroudsburg: ACL, 2018: 16-25. |
[21] | CHEN B, GU X, HU Y, et al. Improving distantly-supervised entity typing with compact latent space clustering[C]// Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, Minneapolis, Jun 2-7, 2019. Stroudsburg: ACL, 2019: 2862-2872. |
[22] | XIN J, ZHU H, HAN X, et al. Put it back: entity typing with language model enhancement[C]// Proceedings of the 2018 Conference on Empirical Methods in Natural Langu-age Processing, Brussels, Oct 31-Nov 4, 2018. Strouds-burg: ACL, 2018: 993-998. |
[23] | ZHANG H, LONG D, XU G, et al. Learning with noise: improving distantly-supervised fine-grained entity typing via automatic relabeling[C]// Proceedings of the 29th Internati-onal Joint Conference on Artificial Intelligence, Yokohama, Jul 2020: 3808-3815. |
[24] | XIA S, WANG G, CHEN Z, et al. Complete random forest based class noise filtering learning for improving the gene-ralizability of classifiers[J]. IEEE Computer Architecture Letters, 2019, 31(11): 2063-2078. |
[25] |
ZHANG W, WANG D, TAN X. Robust class-specific auto-encoder for data cleaning and classification in the presence of label noise[J]. Neural Processing Letters, 2019, 50(2): 1845-1860.
DOI URL |
[26] | WEI Y, GONG C, CHEN S, et al. Harnessing side inform-ation for classification under label noise[J]. IEEE Transa-ctions on Neural networks and Learning Systems, 2019, 31(9): 3178-3192. |
[27] | ZHOU B, KHASHABI D, TSAI C T, et al. Zero-shot open entity typing as type-compatible grounding[C]// Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Oct 31-Nov 4, 2018. Strouds-burg: ACL, 2018: 2065-2076. |
[28] | DAI H, DU D, LI X, et al. Improving fine-grained entity typing with entity linking[C]// Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Hong Kong, China, Nov 3-7, 2019. Stroudsburg: ACL, 2019: 6209-6214. |
[29] | PAN X, CASSIDY T, HERMJAKOB U, et al. Unsuper-vised entity linking with abstract meaning representation[C]// Proceedings of the 2015 Conference of the North Ame-rican Chapter of the Association for Computational Lingu-istics:Human Language Technologies, Denver, May 31-Jun 5, 2015. Stroudsburg: ACL, 2015: 1130-1139. |
[30] | ZHOU P, SHI W, TIAN J, et al. Attention-based bidire-ctional long short-term memory networks for relation classi-fication[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Berlin, Aug 7-12, 2016. Stroudsburg: ACL, 2016: 207-212. |
[31] | WEISCHEDEL R, BRUNSTEIN A. BBN pronoun corefer-ence and entity type corpus[EB/OL]. [2021-01-06]. https://doi.org/10.35111/9fx9-gz10. |
[32] | PENNINGTON J, SOCHER R, MANNING C D. GloVe: global vectors for word representation[C]// Proceedings of the 2014 Conference on Empirical Methods in Natural Lan-guage Processing, Doha, Oct 25-29, 2014. Stroudsburg: ACL, 2014: 1532-1543. |
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[2] | CHENG Qiqin, WAN Liang. Application Research of BiLSTM in Cross-Site Scripting Detection [J]. Journal of Frontiers of Computer Science and Technology, 2020, 14(8): 1338-1347. |
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