Paper Info
Title
Contextual Data Management and Retrieval: A Self-Organized Approach
Abstract
Pervasive computing devices are able to generate enormous amounts of distributed data, from which knowledge about situations and facts occurring in the world should be inferred for the use of pervasive services. However accessing and managing effectively such a huge amount of distributed information is challenging for services. In this paper we propose a self-organized agent-based approach to autonomously organize distributed contextual data items into sorts of knowledge networks. Knowledge networks are conceived as an alive self-organized layer in charge of managing data, that can facilitate services in extracting useful information out of a large amount of distributed items. We present the W4 Data Model we used to represent data and the self-organized approach to build Knowledge Networks. Some experimental
Year
DOI
Venue
2009
10.1109/WI-IAT.2009.343
Web Intelligence/IAT Workshops
Keywords
Field
DocType
data analysis,data model,intelligent agent,information analysis,computer networks,knowledge management,self organization,data models,information retrieval,data management,pervasive computing
Context-aware services,Data mining,Data modeling,Intelligent agent,Contextual information,World Wide Web,Computer science,Contextual design,Context awareness,Ubiquitous computing,Data model
Conference
Volume
ISSN
Citations 
324
1860-949X
2
PageRank 
References 
Authors
0.38
25
2
Name
Order
Citations
PageRank
Gabriella Castelli126320.63
Franco Zambonelli24662330.78