Extraction of the contents in the web texts by content-density distribution
by Saori Kitahara; Koya Tamura; Kenji Hatano
International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP), Vol. 3, No. 2, 2011

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.

Online publication date: Sat, 07-Mar-2015

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