Efficient Notes Generation through Information Extraction
C. Nalini1, Shwetambari Kharabe2, Sangeetha S3
1C.Nalini, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2Shwetambari Kharabe, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
3Sangeetha S, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
Manuscript received on 13 September 2019 | Revised Manuscript received on 22 September 2019 | Manuscript Published on 10 October 2019 | PP: 160-162 | Volume-8 Issue-6S2, August 2019 | Retrieval Number: F10410886S219/19©BEIESP | DOI: 10.35940/ijeat.F1041.0886S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For a specific topic we find several reference books and textbooks to refer and the content is much more than one needs, therefore at the time of revision or quick study we need the summary and short version of the whole content for revision, especially at the time of examinations. There we expect to build up a semi-mechanized method to produce notes from English content records like Reference Books and Text books. The method talked about is viewed as a spearheading endeavor in the field of NLP (Natural Language Processing).This strategy has a wide scope in the instructive space. The procedure when executed as an application can be utilized by both employees and understudies.
Keywords: NLP, Segmentation, Parsing, Ontology.
Scope of the Article: Information Retrieval