Title
Extraction of the contents in the web texts by content-density distribution
Abstract
In recent years, users use result snippets of a web search engine to grasp the content of web pages, when users search for useful information on the internet. However, they are sometimes unable to notice the content of web pages by reading the result snippets because these snippets are so short that they cannot determine whether the content of each web page is relevant. To address this problem, we propose a method for grasping the content of each web page and extracting a part of the web page concerned to query keywords. This method is more effective than conventional methods based on snippets, because we regard the content as a set of words in the text of a web page, and we generate the content-density distribution by using both the position and the influence of the word. In the result of our experiments, we found that our method is useful for gasping the influence of extracted web text.
Year
DOI
Venue
2011
10.1504/IJKESDP.2011.045723
IJKESDP
Keywords
Field
DocType
conventional method,web page,web text,content-density distribution,recent year,web search engine,users search,useful information,result snippet,knowledge engineering
Static web page,Web development,Web search engine,World Wide Web,Information retrieval,Web page,Computer science,Web standards,Backlink,Page view,Dynamic web page
Journal
Volume
Issue
Citations 
3
2
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Saori Kitahara101.01
Koya Tamura201.01
Kenji Hatano33010.41