TY  - JOUR
T1  - Performance Intensification for Automatic Template Using World Wide Web
AU - Sundar, G. Naveen AU - Narmadha, D. AU - Haran, A.P. 
JO  - Research Journal of Applied Sciences
VL  - 9
IS  - 5
SP  - 288
EP  - 294
PY  - 2014
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2014.288.294
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2014.288.294
KW  - Cluster
KW  -non-content path
KW  -template detection
KW  -Minimum Description Length (MDL)
KW  -web
AB  - Every individual is provided with access to plenty of information 
  with the help of world wide web but it becomes progressively more difficult 
  to discover the significant pieces of information. In web mining tries to tackle 
  this problem by applying data mining techniques to web data and documents. The 
  data available on the web is so heterogeneous and huge that it becomes a crucial 
  factor to extract this accessible data to make it pertinent to a particular 
  problem. Web mining uses data mining techniques to extract knowledge from web 
  sources. This study focuses on detecting and extracting templates from web pages 
  that are heterogeneous in nature by means of an algorithm. Locality sensitive 
  hashing finds the similarity between the input web documents and provides good 
  performance compared to the Minimum Description Length (MDL) principle and hash 
  cluster process in terms of execution time.
ER  -