Profile-based focused Crawler for Social Media-Sharing Websites

被引：2
|
作者：
Zhang, Zhiyong [1 ]
Nasraoui, Olfa [1 ]
机构：
[1] Univ Louisville, Dept Comp Sci & Engn, Louisville, KY 40292 USA
来源：
20TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL 1, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICTAI.2008.119
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present a novel profile based focused crawling system for dealing with increasingly popular social media-sharing web sites. In this system, we treat users' profiles as ranking criteria for guiding the crawling process. Furthermore, we divide a user's profile into two parts, an internal part which comes from the user's own contribution, and an external part, which comes from the user's social contacts. In order to efficiently and effectively extract data from a social media-sharing website for focused crawling, a path string based page-classification method was first developed for identifying list pages, detail pages and profile pages.
引用
收藏
页码：317 / 324
页数：8
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