Information Extraction Using Text Mining by Keyword Ranking and Scoring

Authors

  • Gonnade P Depaprtment of Computer Science and engineering, RGCER, Nagpur, India
  • Bongade S Depaprtment of Computer Science and engineering, RGCER, Nagpur, India
  • Mendhe T Depaprtment of Computer Science and engineering, RGCER, Nagpur, India

Keywords:

Extraction, Scores, Text Mining, Page Rank, Clustering, Open Calais

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.

References

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.

Vishal Gupta, Gurpreet S. Lehal,”A Survey of Text Mining Technique and Applications”, Journal of Emerging Technologies in Web Intelligence, Vol. 11, AUGUST 2009.

Namita Gupta,”Text Mining For Information Retrival”, May 2011.

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.

Min Ye,”Text Mining for Building a Biomedical Knowledge Base on Diseases, Risk Factors, and Symptoms”, 2011.

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.

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Published

2014-12-06

How to Cite

[1]
P. Gonnade, S. Bongade, and T. Mendhe, “Information Extraction Using Text Mining by Keyword Ranking and Scoring”, Int. J. Comp. Sci. Eng., vol. 2, no. 11, pp. 50–54, Dec. 2014.

Issue

Vol. 2 No. 11 (2014): IJCSE November Edition

Section

Research Article

License

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