IEEE Style Citation: Priyanka Gonnade, Sarika Bongade , Tushar Mendhe, “Information Extraction Using Text Mining by Keyword Ranking and Scoring,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.50-54, 2014.
MLA Style Citation: Priyanka Gonnade, Sarika Bongade , Tushar Mendhe "Information Extraction Using Text Mining by Keyword Ranking and Scoring." International Journal of Computer Sciences and Engineering 2.11 (2014): 50-54.
APA Style Citation: Priyanka Gonnade, Sarika Bongade , Tushar Mendhe, (2014). Information Extraction Using Text Mining by Keyword Ranking and Scoring. International Journal of Computer Sciences and Engineering, 2(11), 50-54.
BibTex Style Citation:
@article{Gonnade_2014,
author = {Priyanka Gonnade, Sarika Bongade , Tushar Mendhe},
title = {Information Extraction Using Text Mining by Keyword Ranking and Scoring},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2014},
volume = {2},
Issue = {11},
month = {11},
year = {2014},
issn = {2347-2693},
pages = {50-54},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=301},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=301
TI - Information Extraction Using Text Mining by Keyword Ranking and Scoring
T2 - International Journal of Computer Sciences and Engineering
AU - Priyanka Gonnade, Sarika Bongade , Tushar Mendhe
PY - 2014
DA - 2014/11/30
PB - IJCSE, Indore, INDIA
SP - 50-54
IS - 11
VL - 2
SN - 2347-2693
ER -
VIEWS
PDF
XML
3747
3382 downloads
3468 downloads
Abstract
As the number of data is stored in a database, searching of a relevant data is the important issue in text mining. Though the today’s searching method provides us the relevant data but the numbers of results are too big to find the useful data. The needs of the user vary from time to time and they require different information at every instant of time. Keywords are useful for scanning large documents in a short time. Extracting keywords manually are very difficult and time consuming process. In this paper, we present the technique that are most likely able to satisfy the user’s needs and bring useful data in the top positions by extracting keywords from the data present in the database, scoring those keywords based on their occurrences and ranking the data based on keyword scores.
Key-Words / Index Term
Extraction,Scores,Text Mining,Page Rank,Clustering,Open Calais
References
[1] Dilip Kumar Sharma, A. K. Sharma,”A Comparative Analysis of Web Page Ranking Algorithms”, Dilip Kumar Sharma et al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02,,2010.
[2] Vishal Gupta, Gurpreet S. Lehal,”A Survey of Text Mining Technique and Applications”, Journal of Emerging Technologies in Web Intelligence, Vol. 11, AUGUST 2009.
[3] Namita Gupta,”Text Mining For Information Retrival”, May 2011.
[4] Menaka S, RadhaN,”An Overview of Techniques Used for Extracting Keywords from Documents”, International Journal of Computer Trends and Technology (IJCTT) – volume 4, 7–July 2013.
[5] Min Ye,”Text Mining for Building a Biomedical Knowledge Base on Diseases, Risk Factors, and Symptoms”, 2011.
[6] Roberto De Virgilio ,” Efficient and effective ranking in Top-K exploration for Keyword Search on RDF “ Dipartimento di informatica e automazione universita RomaTre, Rome Italy.
VIEWS
PDF 
XML 
