A Detailed Analysis of Core NLP for Information Extraction

International Journal of Machine Learning and Networked Collaborative Engineering, 1(01), 33-47, 2018

15 Pages Posted: 28 May 2019

See all articles by Simran Kaur

Simran Kaur

Manav Rachna International Institute of Research & Studies - Faculty of Computer Applications

Rashmi Agrawal

Manav Rachna International Institute of Research & Studies

Date Written: March 22, 2018

Abstract

The amount of unstructured text present in all electronic media is increasing periodically day after day. In order to extract relevant and succinct information, extraction algorithms are limited to entity relationships. This paper is compendium of different bootstrapping approaches which have their own subtask of extracting dependencies like who did, what, whom, from natural language sentence. This can be extremely helpful in both feature design and error analysis in application of machine learning to natural language processing.

Keywords: Bootstrapping, Language, Lexicon, Unstructured, Corpus, Domain

JEL Classification: Machine Learning, NLP

Suggested Citation

Kaur, Simran and Agrawal, Rashmi, A Detailed Analysis of Core NLP for Information Extraction (March 22, 2018). International Journal of Machine Learning and Networked Collaborative Engineering, 1(01), 33-47, 2018. Available at SSRN: https://ssrn.com/abstract=3376818

Simran Kaur (Contact Author)

Manav Rachna International Institute of Research & Studies - Faculty of Computer Applications ( email )

India

Rashmi Agrawal

Manav Rachna International Institute of Research & Studies ( email )

Delhi Suraj Kund Road
Sector 43
Faridabad, Haryana 121004
India

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