A multi-agent framework for mining semantic relations from Linked Data

作     者：Hua-jun CHEN Tong YU Qing-zhao ZHENG Pei-qin GU Yu ZHANG 

作者机构：School of Computer Science and TechnologyZhejiang UniversityHangzhou 310027China Collegc of InformationZhejiang Sci-Tech UniversityHangzhou 310018China 

出 版 物：《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑（计算机与电子（英文版）)

年 卷 期：2012年第13卷第4期

页      面：295-307页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China (Nos.61070156 and 61100183) the Natural Science Foundation of Zhejiang Province,China (No.Y1110477) 

主　　题：Semantic Web Linked open data Semantic association discovery 

摘      要：Linked data is a decentralized space of interlinked Resource Description Framework(RDF) graphs that are published,accessed,and manipulated by a multitude of Web ***,we present a multi-agent framework for mining hypothetical semantic relations from linked data,in which the discovery,management,and validation of relations can be carried out independently by different *** agents collaborate in relation mining by publishing and exchanging inter-dependent knowledge elements,e.g.,hypotheses,evidence,and proofs,giving rise to an evidentiary network that connects and ranks diverse knowledge *** results show that the framework is scalable in a multi-agent ***-world applications show that the framework is suitable for interdisciplinary and collaborative relation discovery tasks in social domains.