Web Content Mining Using Evolutionary Algorithms: A Survey Report

  Nafisha Mamti

The web surfing has taken place in day to day work that leads to enormous mass of data over the web. The search engines helps to retrieve necessary data from massive databases over the internet. As each search engine has its own limitations to retrieve most relevant information that user is seeking for, user has to struggle to find interesting data from the results provided by traditional search engines. This problem is frequently faced when the user has given complex query i.e. many keywords in search box. To overcome this problem, the search results must be processed further in order to provide most relevant information in proper sequence. Many researchers addressed this issue and has found the various techniques among which the effective one is using evolutionary algorithms. This survey paper summarizes such proposed solutions and enlightens how most relevant information can be produced for complex queries and remove noise. The evolutionary algorithms also used in web pages classification, clustering and feature selection.

Keywords- Web Content mining, Evolutionary Algorithms, Firefly Algorithm, Genetic Relation Algorithm, Memetic Algorithm, feature selection, web page classification, search engine

Unique Identification Number - IJEDR1404083
Page Number(s) - 3901-3905
Pubished in - Volume 2 | Issue 4 | Dec 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Nafisha Mamti,   "Web Content Mining Using Evolutionary Algorithms: A Survey Report", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 4, pp.3901-3905, Dec 2014, Available at :http://www.ijedr.org/papers/IJEDR1404083.pdf