Title :
Intelligent web mining to ameliorate Web Page Rank using Back- Propagation neural network
Author :
Malhotra, Dhairya
Author_Institution :
Dept. of Comput. Sci. & Inf., Univ. of Kota, Kota, India
Abstract :
In a short span of time, less than 15 years, the web search process is modified enormously because of magnificent growth in web based information resources. The speedy expansion of web is enjoyable because of the increase in information resources but at the same time its huge size and interference of SEOs in search process lead to increased difficulty in extracting relevant information from the web. Personalized web search may be the solution to relevancy problem but user is reluctant in giving his personal information because of privacy concerns [1]. Moreover most existing web mining algorithms do not possess attractive time and space complexities and hence lead to sufferings of novice user. This paper addresses above mentioned issues of Search Engine domain and intends to implement intelligent web mining in the form of Web Page Ranking Tool so as to improve the web page ranking process through incorporation of Back Propagation neural networks. [2][3][4].
Keywords :
backpropagation; computational complexity; data mining; data privacy; neural nets; search engines; Web based information resources; Web page ranking tool; Web search process; back-propagation neural network; intelligent Web mining; personalized Web search; privacy concerns; relevant information extraction; search engine domain; space complexity; time complexity; Business; Neural networks; Optimization; Search engines; Web mining; Web pages; Back Propagation Neural Networks; Intelligent Mining; Web Neural Mining; Web Page Ranking;
Conference_Titel :
Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -
Conference_Location :
Noida
Print_ISBN :
978-1-4799-4237-4
DOI :
10.1109/CONFLUENCE.2014.6949254