0000000000110634
AUTHOR
Vadim Ermolayev
Large Scale Knowledge Matching with Balanced Efficiency-Effectiveness Using LSH Forest
Evolving Knowledge Ecosystems were proposed to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investigate the u…
Large Scale Knowledge Matching with Balanced Efficiency-Effectiveness Using LSH Forest
Evolving Knowledge Ecosystems were proposed to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investigate the u…
Balanced Large Scale Knowledge Matching Using LSH Forest
Evolving Knowledge Ecosystems were proposed recently to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investig…
Towards a Framework for Agent-Enabled Semantic Web Service Composition
The article presents the framework for agent-enabled dynamic Web service composition. The core of the methodology is the new understanding of a Web service as an agent capability having proper ontological description. It is demonstrated how diverse Web services may be composed and mediated by dynamic coalitions of software agents collaboratively performing tasks for service requestors. Middle Agent Layer is introduced to conduct service request to task transformation, agent-enabled cooperative task decomposition and performance. Discussed are the formal means to arrange agents’ negotiation, to represent the semantic structure of the task-activity-service hierarchy and to assess fellow-agent…
Linked Data in Enterprise Integration
Proactively Composing Web Services as Tasks by Semantic Web Agents
This chapter presents the framework for agent-enabled dynamic composition of Semantic Web services. The approach and the framework have been developed in several research and development projects by ISRG and IOG. The core of the methodology is the new understanding of a Semantic Web service as a capability of an intelligent software agent supplied with the proper ontological description. It is demonstrated how diverse Web services may be composed and mediated by dynamic coalitions of software agents collaboratively performing tasks for service requestors. Middle agent layer is introduced to conduct the transformation of a Web service request to the corresponding task, agent-enabled cooperat…