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Event Extraction from Twitter using Scoring Function and LDA

Monika Gupta1 , Parul Gupta2

  1. Computer Science, Y.M.C.A. University of Science and Technology, Faridabad, India.
  2. Computer Science, Y.M.C.A. University of Science and Technology, Faridabad, India.

Correspondence should be addressed to: monika.mittal167@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-2 , Page no. 98-103, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i2.98103

Online published on Feb 28, 2018

Copyright © Monika Gupta, Parul Gupta . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Monika Gupta, Parul Gupta, “Event Extraction from Twitter using Scoring Function and LDA,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.2, pp.98-103, 2018.

MLA Style Citation: Monika Gupta, Parul Gupta "Event Extraction from Twitter using Scoring Function and LDA." International Journal of Computer Sciences and Engineering 6.2 (2018): 98-103.

APA Style Citation: Monika Gupta, Parul Gupta, (2018). Event Extraction from Twitter using Scoring Function and LDA. International Journal of Computer Sciences and Engineering, 6(2), 98-103.

BibTex Style Citation:
@article{Gupta_2018,
author = {Monika Gupta, Parul Gupta},
title = {Event Extraction from Twitter using Scoring Function and LDA},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2018},
volume = {6},
Issue = {2},
month = {2},
year = {2018},
issn = {2347-2693},
pages = {98-103},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1707},
doi = {https://doi.org/10.26438/ijcse/v6i2.98103}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i2.98103}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1707
TI - Event Extraction from Twitter using Scoring Function and LDA
T2 - International Journal of Computer Sciences and Engineering
AU - Monika Gupta, Parul Gupta
PY - 2018
DA - 2018/02/28
PB - IJCSE, Indore, INDIA
SP - 98-103
IS - 2
VL - 6
SN - 2347-2693
ER -

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Abstract

Extracting and interpreting information from user generated content is a current topic in the scientific community and in the business world. Furthermore, data with a spatial component are even more important. This is proved by the numerous web applications that deal with processing and visualization of user generated content. The task of this extraction is to collect major life events in the form of retrievable entries that include structured data about major life event name, location and time which are often, categorized by complex, and nested structures involving ambiguous entities.

Key-Words / Index Term

Events, tweets, LDA, Extraction

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