The Research of Personalized Intelligent Information Retrieval System Based on the Domain Ontology about Tea-Worm

2010 ◽  
Author(s):  
Xu Gaojian ◽  
Li Shaowen
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Intelligent Information Retrieval ◽  
Intelligent Information

Research on Domain Ontology-Based Intelligent Information Retrieval System

2011 ◽  
Vol 460-461 ◽  
pp. 300-304
Author(s):  
Shu Dong Zhang ◽  
Yan Chen
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Rapid Development ◽  
Relevant Information ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Information Resources ◽  
Semantic Level ◽  
Intelligent Information Retrieval ◽  
Intelligent Information

Domain ontology introduces a new theory and method for information retrieval. In this paper, we analyze the deficiencies of traditional information retrieval and explore the relationship between domain ontology and information retrieval, as well as the basic design ideas of information retrieval based on domain ontology. Finally we present a domain ontology-based intelligent information retrieval system, so that the information retrieval can be promoted from the keyword level to the semantic level. With the rapid development of the national economy and the growth of information resources, traditional methods relying on the browser, database fields, keyword matching, or even manual retrieval query has become increasingly difficult to meet people's information retrieval needs. How to quickly and accurately identify the needed information resources has become a urgent question in front of us. Information retrieval is a technology which can find out the relevant information the user needs from a collection of large amounts of information. It has experienced manual retrieval, computer retrieval stage, now it has developed to the network and intelligent stage. The objects of information retrieval extend from a relative closed, stable and consistent, centrally managed information content by an independent database to an open, dynamic, quickly update, widely distributed, and loosely managed web content; the users of information retrieval also spread from professional intelligence agent to the common including government officials, businessmen, managers, teachers, students, professionals, etc. They ask for the higher and more diverse requirements from the results to the manner of information retrieval. Adapting to the need for network, intelligence and personalization is a new trend of information retrieval technology.

Intelligent Information Retrieval System Based on Muti-Agent Model

2013 ◽  
Vol 765-767 ◽  
pp. 1529-1532
Author(s):  
Zhao Dan Wu ◽  
Chang Feng Shi ◽  
Yi Lu
Keyword(s):  
Information Retrieval ◽  
Cognitive Theory ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Theoretical Derivation ◽  
Agent Model ◽  
Intelligent Information Retrieval ◽  
Multi Agent ◽  
Agent Intelligence ◽  
Intelligent Information

The intelligent information retrieval model discussed in this paper is constructed by multi-agent. Currently, BDI cognitive theory is accepted widely by the scholars of this field, but the related researches mainly focus on the theoretical derivation and presentation of symbols, lack of model facing practical application. In this article, a dynamic rule-based reasoning model is proposed. The model based on BDI theory is an expression of agent intelligence. The basic logical reasoning of the BDI theory is extended in this article. The author not only introduces several functions to study the dynamic changes of agents mental state, but also give a detailed description of how to use the theory of production rules to express BDI-based reasoning. This article also studies and designs the agent communication mechanism in MAS. Finally, the intelligent information retrieval system is designed and implemented with the idea of AOP.

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