Call for Paper - November 2023 Edition
IJCA solicits original research papers for the November 2023 Edition. Last date of manuscript submission is October 20, 2023. Read More

A System to Determine Demographic Attributes using Local Browsing History

Print
PDF
 
Download Full Text
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 171 - Number 4
Year of Publication: 2017
Authors:
Siddhesh Karekar, Amogh Bhabal, Bhushan Pathak, Swati Mali
10.5120/ijca2017915012

Siddhesh Karekar, Amogh Bhabal, Bhushan Pathak and Swati Mali. A System to Determine Demographic Attributes using Local Browsing History. International Journal of Computer Applications 171(4):8-12, August 2017. BibTeX

@article{10.5120/ijca2017915012,
	author = {Siddhesh Karekar and Amogh Bhabal and Bhushan Pathak and Swati Mali},
	title = {A System to Determine Demographic Attributes using Local Browsing History},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2017},
	volume = {171},
	number = {4},
	month = {Aug},
	year = {2017},
	issn = {0975-8887},
	pages = {8-12},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume171/number4/28167-2017915012},
	doi = {10.5120/ijca2017915012},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The internet is a large storehouse of information. To deliver information efficiently, the audience can be segregated by demographic attributes which can be individually targeted. Companies may be able to obtain or collect information about users' browsing history. Proposed in this paper is a system using TF-IDF and a Neural network, to estimate a user's age, gender and interests by analyzing their browser history.

References

  1. Grčar, M., Mladenič, D., & Grobelnik, M. (2005). User profiling for interest-focused browsing history. In Proceedings of the Workshop on End User Aspects of the Semantic Web (pp. 99-109).
  2. Hawalah, A., & Fasli, M. (2015). Dynamic user profiles for web personalisation. Expert Systems with Applications, 42(5), 2547-2569.
  3. Swami, C. P., Tarte, P. B., Rakshe, S. K., Raut, S. M., & Shaikh, N. F. (2015). Detecting the age of a person through web browsing patterns. International Journal of Computer Applications, 118(12).
  4. Porter, M. (2008). The Porter stemming algorithm, 2005. http://www. tartarus. org/martin/PorterStemmer/index. html. Last visited on July, 16.
  5. Swami, C., Tarte, P., Rakshe, S., Raut, S., & Shaikh, N. F. Detecting the age of a person through web browsing patterns: A Review. International Journal of Soft Computing and Engineering (IJSCE) ISSN, 2231-2307.
  6. Jang, J. S. R., Sun, C. T., & Mizutani, E. (1997). Neuro-fuzzy and soft computing, a computational approach to learning and machine intelligence.

Keywords

Demographic, browser, history, user, gender, age, estimation, location, prediction.