Title
A Case Study On Domain Analysis Of Semantic Web Multi-Agent Recommender Systems
Abstract
The huge amount of data available on the Web and its dynamic nature is the source of an increasing demand of information filtering applications such as recommender systems. The lack of semantic structure of Web data is a barrier for improving the effectiveness of this kind of applications. This paper introduces ONTOSERS-DM, a domain model that specifies the common and variable requirements of Recommender Systems based on the ontology technology of the Semantic Web, using three information filtering approaches: content-based, collaborative and hybrid filtering. ONTOSERS-DM was modeled under the guidelines of MADEM, a methodology for Multi-Agent Domain Engineering, using the ONTOMADEM tool.
Year
Venue
Keywords
2008
ICSOFT (ISDM/ABF)
Recommender Systems, Semantic Web, information filtering, Domain Engineering, Multi-agent systems
Field
DocType
Citations 
Recommender system,World Wide Web,Information retrieval,Semantic search,Semantic Web Stack,Computer science,Semantic Web,Data Web,Semantic analytics,Social Semantic Web,Semantic computing
Conference
2
PageRank 
References 
Authors
0.43
1
5
Name
Order
Citations
PageRank
Roberval Mariano120.43
Rosario Girardi220.43
Adriana Leite320.43
Lucas Drumond439524.27
Djefferson Maranhão521.11