Abstract
Entity extraction is an important task in text mining and natural language processing. A popular method for entity extraction is by comparing substrings from free text against a dictionary of entities. In this paper, we present several techniques as a post-processing step for improving the effectiveness of the existing entity extraction technique. These techniques utilise models trained with the web-scale corpora which makes our techniques robust and versatile. Experiments show that our techniques bring a notable improvement on efficiency and effectiveness.
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References
Bengio, Y., Ducharme, R., Vincent, P., Jauvin, C.: A neural probabilistic language model. J. Mach. Learn. Res. 3(Feb), 1137–1155 (2003)
Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. Trans. Assoc. Comput. Linguist. 4, 357–370 (2016)
Corbet, S.A., Delfosse, E.S.: Honeybees and the nectar of echium plantagineum l. in Southeastern Australia. Aust. J. Ecol. 9(2), 125–139 (1984)
Harper, F.M., Konstan, J.A.: The movielens datasets: history and context. ACM Trans. Interact. Intell. Syst. (TIIS) 5(4), 19 (2016)
Heafield, K.: KenLM: faster and smaller language model queries. In: Workshop on Statistical Machine Translation, pp. 187–197. ACL (2011)
Jagadish, H.V., Ooi, B.C., Tan, K.-L., Yu, C., Zhang, R.: iDistance: an adaptive B+-tree based indexing method for nearest neighbor search. Trans. Database Syst. 30(2), 364–397 (2005)
Lin, Y., Michel, J.-B., Aiden, E.L., Orwant, J., Brockman, W., Petrov, S.: Syntactic annotations for the google books ngram corpus. In: ACL, pp. 169–174 (2012)
Maas, A.L., Daly, R.E., Pham, P.T., Huang, D., Ng, A.Y., Potts, C.: Learning word vectors for sentiment analysis. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 142–150. Association for Computational Linguistics (2011)
McAuley, J., Leskovec, J.: Hidden factors and hidden topics: understanding rating dimensions with review text. In: Proceedings of the 7th ACM Conference on Recommender Systems, pp. 165–172. ACM (2013)
Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, pp. 3111–3119 (2013)
Mikolov, T., Yih, W.-T., Zweig, G.: Linguistic regularities in continuous space word representations. In: Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–751 (2013)
Pauls, A., Klein, D.: Faster and smaller n-gram language models. In: ACL, pp. 258–267. ACL (2011)
Tseytlin, E., Mitchell, K., Legowski, E., Corrigan, J., Chavan, G., Jacobson, R.S.: Noble-flexible concept recognition for large-scale biomedical natural language processing. BMC Bioinf. 17(1), 32 (2016)
Wei, Q., Chen, T., Xu, R., He, Y., Gui, L.: Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks. Database 2016 (2016)
Wen, Z., Deng, D., Zhang, R., Kotagiri, R.: An efficient entity extraction algorithm using two-level edit-distance. In: ICDE, pp. 998–1009. IEEE (2019)
Wen, Z., Zhang, R., Ramamohanarao, K., Qi, J., Taylor, K.: MASCOT: fast and highly scalable SVM cross-validation using GPUs and SSDs. In: ICDM, pp. 580–589. IEEE (2014)
Whitelaw, C., Hutchinson, B., Chung, G.Y., Ellis, G.: Using the web for language independent spellchecking and autocorrection. In: EMNLP, pp. 890–899. ACL (2009)
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Wen, Z., Huang, Z., Zhang, R. (2020). Entity Extraction with Knowledge from Web Scale Corpora. In: Borovica-Gajic, R., Qi, J., Wang, W. (eds) Databases Theory and Applications. ADC 2020. Lecture Notes in Computer Science(), vol 12008. Springer, Cham. https://doi.org/10.1007/978-3-030-39469-1_14
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DOI: https://doi.org/10.1007/978-3-030-39469-1_14
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