Paper Info
Title
Textual Knowledge Flow Based Intelligent Browsing of Topics
Abstract
Textual Knowledge Flow (TKF) provides an effective technique and theoretical support for intelligent browsing. In order to realize the intelligent browsing of topics in Web or Library, TKF based intelligent browsing of topics is proposed. Firstly, topics are represented by Element Fuzzy Cognitive Maps (E-FCMs); then semantic values of concepts and semantic influences of relations are calculated based on their frequencies and weights in E-FCMs library. Thirdly, semantic similarity degrees between topics are calculated for building the Semantic Link Network (SLN). Fourthly, with the help of SLN and user's demand, TKF between similar topics is activated as browsing path of topics to guide user's browsing behavior. Experimental results show that the browsing path of topics is easy to be built by the proposed method. TKF based topic browsing has a brilliant perspective in the applications of intelligent browsing, knowledge grid and semantic Web.
Year
DOI
Venue
2008
10.1109/GPC.WORKSHOPS.2008.61
GPC Workshops
Keywords
Field
DocType
topic browsing,element fuzzy cognitive maps,semantic influence,semantic link network,browsing path,intelligent browsing,information retrieval,knowledge grid,textual knowledge flow,semantic value,library,element fuzzy cognitive map,semantic similarity degree,e-fcms library,knowledge engineering,semantic web,semantic values,semantic similarity,knowledge management,fuzzy cognitive map,fuzzy cognitive maps,machine intelligence,grid computing,text analysis,frequency,pervasive computing
Semantic similarity,Grid computing,Information retrieval,Computer science,Fuzzy cognitive map,Semantic Web,Knowledge engineering,Ubiquitous computing,Grid,Knowledge flow
Conference
ISBN
Citations 
PageRank 
978-0-7695-3177-9
3
0.51
References 
Authors
6
5
Name
Order
Citations
PageRank
Xiangfeng Luo11251124.38
Qingliang Hu2382.79
Fangfang Liu3819.04
Jie Yu44110.55
Xinhuai Tang55011.53