HYBRID NEWS RECOMMENDATION SYSTEM USING TF-IDF AND ASSOCIATIVE CALCULUS
Rachana Naik
, Abhishek Raghuvanshi
TF-IDF, News, BBC Dataset, Associative Calculus
The growing use of internet makes it essential for daily life. It plays important role in busy schedule to make it easy and simple. The bigger challenge of today is awareness of current affairs. Data mining techniques is the results of an extended method of analysis and merchandise development. Data mining takes this organic process on the far side retrospective knowledge access and navigation to prospective and proactive data delivery. Recommender systems is one of the biggest outcome of data mining gives more relevant and useful outcome NEWS Recommender systems have created important space in daily routing life. Newspapers are essential to urge information concerning recent activity and general awareness. Varied solutions are developing to convert paper News system to digital news and become an excessive amount of standard. This paper has investigated the importance of news recommendation solution and effort to improve the performance of news recommendation using modified TF-IDF algorithm. Proposed solution is implemented using Java technology and evaluated on basis of computation time for different category. A BBC dataset has been used as data source for same.
"HYBRID NEWS RECOMMENDATION SYSTEM USING TF-IDF AND ASSOCIATIVE CALCULUS", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 3, page no.48 - 51, March-2017, Available :https://ijsdr.org/papers/IJSDR1703008.pdf
Volume 2
Issue 3,
March-2017
Pages : 48 - 51
Paper Reg. ID: IJSDR_170076
Published Paper Id: IJSDR1703008
Downloads: 000347161
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
