Paper Info
Title
Ranking Web Page with Path Trust Knowledge Graph.
Abstract
How to find and discover useful information from Internet is a real challenge in information retrieval IR and search engines SE. In this paper, we propose and construct Path Trust Knowledge Graph PTKG model for assigning priority values to the unvisited web pages. For a given user specific topic t, its PTKG contains five parts: 1 The context graph $$Gt=V, E$$, where V is the crawled history web page set and E includes the hyper link set among the history web pages; 2 Retrieving knowledge implied in the paths among these web pages and finding their lengths; 3 Building the trust degrees among the web pages; 4 Constructing topic specific language model and general language model by using the trust degrees; 5 Assigning the priority values of web pages for ranking them. Finally, we perform an experimental comparison among our proposed PTKG approach with the classic LCG and RCG. As a result, our method outperforms LCG and RCG.
Year
DOI
Venue
2015
10.1007/978-3-319-23862-3_7
IScIDE
Keywords
Field
DocType
Knowledge graph, Path trust degree, Topic-specific crawlers
Graph,Knowledge graph,World Wide Web,Search engine,Information retrieval,Ranking,Web page,Computer science,Website Parse Template,Language model,The Internet
Conference
Volume
ISSN
Citations 
9243
0302-9743
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
YaJun Du19622.51
Qiang Hu200.34
Xiaolei Li300.34
Xiaoliang Chen46816.42
Chenxing Li5146.76