Algorithms for clustering data
Algorithms for clustering data
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
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
IEEE Internet Computing
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
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Dealing with semantic heterogeneity for improving web usage
Data & Knowledge Engineering - Special issue: ER 2004
Agents' roles in B2C e-commerce
AI Communications
An optimized hierarchical model for agent-mediated e-commerce
MCBE'07 Proceedings of the 8th Conference on 8th WSEAS Int. Conference on Mathematics and Computers in Business and Economics - Volume 8
Agent clustering based on semantic negotiation
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Multiagent based large data clustering scheme for data mining applications
AMT'10 Proceedings of the 6th international conference on Active media technology
An approach for clustering semantically heterogeneous XML schemas
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
An ontology-based two-level clustering for supporting e-commerce agents' activities
EC-Web'05 Proceedings of the 6th international conference on E-Commerce and Web Technologies
Cloning mechanisms to improve agent performances
Journal of Network and Computer Applications
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In this paper we propose an agent-based hierarchical clustering technique operating on both user profiles and e-commerce sites. We show, by designing a number of appealing applications, how exploitation of such hierarchies can really benefit both customers and vendors in their activity. As a support for the customer, we provide a categorization of sites of interest as she/he perceives them, and also dynamic ecommerce portal personalization. As a support for the vendor, we design a categorization of customers directly supporting knowledge discovery on customer behavior.