Intelligent personalised information retrieval system based on multi-agent

2011 ◽  
Vol 12 (1/2) ◽  
pp. 113 ◽  
Author(s):  
Yan Li ◽  
Fuwen Guo ◽  
Xiufeng Wang
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Multi Agent

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.

Research of Personalized Intelligent Information Retrieval System Based on Agent

2014 ◽  
Vol 945-949 ◽  
pp. 3406-3409
Author(s):  
Ying Hong
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Knowledge Database ◽  
Multi Agent ◽  
Intelligent Information ◽  
User Knowledge ◽  
Ranking Analysis ◽  
Model Algorithm

To efficiently retrieve information from the vast source of the internet, search engines are required. There are some search engines that can help people to search for needed information, but they are difficult to ensure precision rate and personalization of information. To solve these problems, this paper proposed a personalized information retrieval system based on meta-search engine. This paper used multi-agent technology to construct the personalized information retrieval system, adopted user knowledge database to create and update user model and improved vector space model algorithm combining with user knowledge database which used in results ranking. Analysis and experiment show that personalized information retrieval system implemented in this paper can improve the precision ratio and can meet the needs of the user's personality requirements.

scholarly journals A Multi-Agent Based Approach to Short Message Service (SMS) Normalization System

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Olusola Adesina
Keyword(s):  
Information Retrieval ◽  
Short Message Service ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Short Message ◽  
Human Judgment ◽  
Web Information Retrieval ◽  
Web Information ◽  
Message Service ◽  
Multi Agent

SMS language is characterized by fashion and user’s creativity but needs a transformation to proper English words or spelling to formulate natural language and text processing activities. The proposed application, Web Information Retrieval System Architecture Based on SMS (WIRSABoSMS), normalizes SMS language to retain its original syntactic structure. The concept of mobile agents in web technology was introduced as a medium to achieving Short Message Service (SMS) normalization. SMS normalization was carried out with the adoption of multi-agent technology, as agents are involved in character search, sort, and compare of the strings written in SMS form into its parental orthography. This architecture was designed based on web information retrieval system (IRS) in order to achieve SMS normalization. BLEU (bilingual evaluation understudy) was used to evaluate the quality of text. BLEU scores compare the human judgment with that of the machine translation using two set of corpora. The outcome of syntactic text message normalization recorded an average of 90% performance (for the corpus collected from researchers) when compared with the similar test conducted with human judgment using BLEU scores metric in an health-related domain.

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