The week's pick
Reseach Article
Enhanced Term � Document Frequency Classification Approach for Personalizing News Items
| International Conference and Workshop on Emerging Trends in Technology |
| Foundation of Computer Science USA |
| ICWET - Number 2 |
| None 2011 |
| Authors: S.Akhilan, S.R.Balasundaram |
| 717bcd73-e121-41cb-8412-bb95d8729f1d |
S.Akhilan, S.R.Balasundaram . Enhanced Term � Document Frequency Classification Approach for Personalizing News Items. International Conference and Workshop on Emerging Trends in Technology. ICWET, 2 (None 2011), 1-7.
Abstract
Speedy growth of internet technologies has provided sufficient ways and mechanisms to provide any information to any person about any entity irrespective of time and place. Getting knowing what had happened around an individual in their living place is an essential requirement in this modern world. This is achieved with the help of various news service providers such as yahoo, google, your news etc. While delivering news to its users most of the news service providers do not take into the account the users choice or interests for information content delivery. Providing all news to all will not be an appropriate one when there exists different class of viewers. This major problem can be solved by adopting personalization and it is the key factor which aims at providing the appropriate data for the related person. It is most essential to personalize the news documents such that users can be made comfort by delivering the news of their preferences or interests. In this paper, we have proposed a classification method named enhanced Term-Document Frequency (eTF-IDF) method, by which sports news documents of three varied categories are classified and made personalized as per the users interests.
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