What is it about?

The paper presents the architecture of the system to retrieve information for a university environment. The architecture based on multi-agent concept. Main properties of the proposed system are its user orientation and learnability, which is possible by adding new terms to the ontology and relating them with terms, stored in the System. The queries could be presented in the natural language. The System provides transparency of the information resources. The architecture of the system is composed of 3 type agents: user agent, communication agent and information retrieving agents. Communications between the Communication Agent and the other agents are realized via the Communication Module. The module works on the SOAP protocols, which are high level messaging protocols based on XML. The developed system works on a distributed environment, where component agents collaborate via XML Web Services and SOAP protocols.

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Why is it important?

In performing routine tasks, in developing rapport, for decision support and decision making, people spend much time in finding, filtering and processing necessary information. The effort is increasing, if the information is located in heterogeneous sources with different presentation, and access to it requires different methods. To retrieve different types of information from multiple sources it is necessary to create integrated system, where for all types of information, system must be able to process user queries for all types of information, in depending of the context and structure of the queries

Perspectives

The approach proposed in the work provides the flexibility of integrating of any information retrieval model with any type of database management system. This framework makes possible the systematic investigation of the potential of using information retrievals models as a general tool for supporting management decisions

Dmitriy Bystrov
Tashkent State Technical University named after Islam Karimov

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This page is a summary of: Performing and proposition of network selection organized on multiple factors in diverse settings, January 2024, American Institute of Physics,
DOI: 10.1063/5.0241848.
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