To identify the usage of clustering techniques for improving search result of a website

Shashi Mehrotra, Shruti Kohli and Aditi Sharan

International Journal of Data Mining, Modelling and Management, 2018, vol. 10, issue 3, 229-249

Abstract: Clustering has drawn much attention to research community due to its advantages and wide applications. However, clustering is a challenging problem, as many factors play a significant role. The same algorithm may generate different output if there is a change in parameters, presentation order or similarity measure. The search option is used excessively on almost every website. Grouping the search results in various folders will improve web browsing and that can be achieved by applying clustering over results. Clustering web elements facilitate data analysis in various ways. In this paper, we present well-known clustering algorithms and identify their different usages for the web elements. The paper discusses some significant work conducted in this field.

Keywords: clustering algorithm; distance measure; web analytics; complexity. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=93879 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdmmm:v:10:y:2018:i:3:p:229-249

Access Statistics for this article

More articles in International Journal of Data Mining, Modelling and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().