WordNet: a lexical database for English
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
Semantic integration of semistructured and structured data sources
ACM SIGMOD Record
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Incremental clustering for profile maintenance in information gathering web agents
Proceedings of the fifth international conference on Autonomous agents
Global Viewing of Heterogeneous Data Sources
IEEE Transactions on Knowledge and Data Engineering
A Graph-Based Approach For Extracting Terminological Properties of Elements of XML Documents
Proceedings of the 17th International Conference on Data Engineering
Using Schema Matching to Simplify Heterogeneous Data Translation
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Ontology Based Personalized Search
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
X-Compass: An XML Agent for Supporting User Navigation on the Web
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Annals of Mathematics and Artificial Intelligence
Knowledge and Information Systems
An XML-based agent model for supporting user activities on the Web
Web Intelligence and Agent Systems
Hi-index | 0.00 |
In this paper we propose a user profile based approach forsupporting Web-oriented search. Differently from traditionalsyntax-based approaches, our method is semantic driven. Indeed, foreach user, a profile is constructed and handled for representingher/his interests. Whenever a user submits a query, a classical Websearch engine is activated for determining a (probably large) setof answer data sources. After this, the user profile is exploitedfor determining the subset of those data sources which bestconforms to user interests. In order to semantically compare thecontent of a data source with a user profile, a formal inferenceframework, provided by a specialized probabilistic variant ofDescription Logics, is exploited.