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Evaluation of Clustering Techniques for News Recommendation

By Gatla, Ranjith Kumar

Evaluation of Clustering Techniques for News Recommendation Computer Science

Evaluation of Clustering Techniques for News Recommendation

0 - Default Title
Description
The information overloading is one of the most significant issues nowadays. It can be seen in different domains, consisting of business, particularly in news. This is more important in link to news websites and web, where the news websites reliability is typically determined by quantity of news added to the portal. Then the most popular news websites include numerous of news articles daily. The classical solution generally used to address the information overloading is a recommendation. In this book we evaluate the MapReduce k-means and fuzzy k-means clustering for a content-based recommendation for news articles, based on Euclidian distance and cosine similarity search. This approach consists of two phases of operation.
Product details
Binding:
Paperback
Number of Pages:
60
Release Date:
2025-04-16
Publication Date:
2025-04-16
Publisher:
LAP LAMBERT Academic Publishing
Languages:
Original: English
ISBN10:
6208442435
ISBN13:
9786208442439
GPSR Manufacturer Reference:
[email protected]
Weight:
107 g
Height:
150 cm
Width:
220 cm
Thickness:
4 cm
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