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A Web Recommender System using User Logs Files with k-NN Method

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Anupama Patel, Santosh K. Vishwakarma

Anupama Patel and Santosh K Vishwakarma. A Web Recommender System using User Logs Files with k-NN Method. International Journal of Computer Applications 175(1):26-30, October 2017. BibTeX

	author = {Anupama Patel and Santosh K. Vishwakarma},
	title = {A Web Recommender System using User Logs Files with k-NN Method},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2017},
	volume = {175},
	number = {1},
	month = {Oct},
	year = {2017},
	issn = {0975-8887},
	pages = {26-30},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017915468},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In the current era there is a huge increment in the generation of web data. Internet is getting overloaded with the massive increase in data. This unstable growth in information is making the search a complicate process. This in result has given rise to a new idea to analysis the system. Web recommender system is the most efficient solution for the problem and is widely used in e-commerce websites to suggest product in reference to the user request. Giving suggestion is not an easy task, whereas it not only helps in saving time but also helps in decision making. Web servers contain log files these log files have records of events in the sequential pattern. Sequential information gives the detail information about the user’s behavior. In this paper k-NN method is implemented to obtain the prediction for the new users. The dataset used in this paper is the dummy dataset.


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Web recommender system, sequential information, web server, log files, k-NN.