Abstract
Designing intelligent expert systems capable of answering different human queries is a challenging and emerging area of research. A huge amount of Web resources are available these days and majority of which are in the form of unstructured documents covering articles, corporate reports, online news, medical records, social media communication data, etc. A user in need of certain information has to assess all the relevant documents to obtain the answer of their queries which is a time-consuming and tedious work. Also, sometimes it becomes quite difficult to obtain the exact information from a list of documents quickly as and when required. This work aims to designing an intelligent information extraction system, which accesses the document contents quickly and provides the relevant answers to the user queries in a structured format just like a human expert answers to the questions.
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References
Glauber, R., Claro, D.B.: A systematic mapping study on open information extraction. Expert Syst. Appl. Elsevier 112, 372–387 (2018)
Rajbabu, K., Srinivas, H., Sudha, S.: Industrial information extraction through multi-phase classification using ontology for unstructured documents. Comput. Indust. Elsevier 100, 137–147 (2018)
Chen, G., Wang, C., Zhang, M., Wei, Q., Ma, B.: How small reflects large?—representative information measurement and extraction. Inf. Sci. Elsevier 460, 519–540 (2017)
Wang, Y., Wang, L., Rastegar-Mojarad, M., Moon, S., Shen, F., Afzal, N., Liu, S., Zeng, Y., Mehrabi, S., Sohn, S., Liu, H.: Clinical information extraction applications: a literature review. J. Biomed. Inform. Elsevier 77, 34–49 (2017)
Aramaki, E., Maskawa, S., Morita, M.: Twitter catches the flu: detecting influenza epidemics using twitter. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1568–1576 (2011)
Uchun Peng, F., McCallum, A.: Information extraction from research papers using conditional random fields. Int. J. Inform. Process. Manage 42, 963–979 (2006)
Atkinson-Abutridy, J., Mellish, C., Aitken, S.: Combining information extraction with genetic algorithms for text mining. IEEE Intell. Syst. 19, 22–30 (2004)
Senga, J., Laib, J.T.: An Intelligent information segmentation approach to extract financial data for business valuation. Elsevier J. Exp. Syst. Appl. 37, 6515–6530 (2010)
Han, H., Giles, C.L., Manavoglu, E., Zha, H., Zhang, Z., Fox, E.A.: Automatic document metadata extraction using support vector machines. In: Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries, vol. 37–48 (2003)
Munger, T., Desa, S., Wong, C.: The use of domain knowledge models for effective data mining of unstructured customer service data in engineering applications. In: IEEE First International Conference on Big Data Computing Service and Applications, pp. 427–438 (2015)
Norman, B., Davis, T., Quinn, S., Massey, R., Hirsh, D.: Automated identification of pediatric appendicitis score in emergency department notes using natural language processing. In: IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 481–485 (2017)
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Pradhan, A., Behera, V., Mohanty, A., Panda, S.P. (2020). A Voice-Based Information Extraction System. In: Satapathy, S., Bhateja, V., Mohanty, J., Udgata, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 159. Springer, Singapore. https://doi.org/10.1007/978-981-13-9282-5_56
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DOI: https://doi.org/10.1007/978-981-13-9282-5_56
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