A fuzzy information retrieval and management system and its applications

1996 ◽  
Author(s):  
Pascal Subtil ◽  
Noureddine Mouaddib ◽  
Odile Foucaut
Keyword(s):  
Information Retrieval ◽  
Management System ◽  
Fuzzy Information ◽  
Fuzzy Information Retrieval

Semantic / Fuzzy Information Retrieval System

2017 ◽  
Vol 12 (1) ◽  
pp. 37-56
Author(s):  
Mounira Chkiwa ◽  
Anis Jedidi ◽  
Faiez Gargouri
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Semantic Web ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Retrieval Process ◽  
Fuzzy Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Fuzzy Information Retrieval

In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.

An Enhanced Fuzzy Information Retrieval Model Based on Linguistics

2014 ◽  
Vol 519-520 ◽  
pp. 853-856
Author(s):  
Zeinab E. Al-Arab ◽  
Ahmed M. Gadallah ◽  
Hesham M. Hefny
Keyword(s):  
Information Retrieval ◽  
Ranking Algorithm ◽  
Retrieval Model ◽  
Fuzzy Information ◽  
Model Based ◽  
Fuzzy Ontology ◽  
Confidence Degree ◽  
Subjective View ◽  
Fuzzy Information Retrieval

The paper proposes a linguistic based fuzzy ontology information retrieval model. The model deals with linguistic based queries in multi domains. Such linguistics are user defined, reflecting his subjective view. The model also proposes a ranking algorithm that ranks the set of relevant documents according to some criteria such as their relevance degree, confidence degree, and updating degree.

Fuzzy Information Retrieval Method Based on Fuzzy-Valued Concept Networks

2014 ◽  
Vol 530-531 ◽  
pp. 506-511
Author(s):  
Liu Yang Wang ◽  
Yang Xin Yu ◽  
Lei Zhou ◽  
Sheng Hua Jin
Keyword(s):  
Information Retrieval ◽  
Network Architecture ◽  
Fuzzy Inference ◽  
Positive Association ◽  
Relationship Matrix ◽  
Fuzzy Information ◽  
Retrieval Method ◽  
Information Retrieval Systems ◽  
Fuzzy Information Retrieval ◽  
Concept Network

In order to reduce the time of fuzzy inference, the relevant matrices and the relationship matrices are used to constitute the fuzzy-valued concept networks. The elements of a relevant matrix represent the relevant degrees between concepts. The elements of a relationship matrix represent the relevant relationships between concepts. Fuzzy positive association relationship or fuzzy negative association relationship are used for formulating users queries in order to increase the flexibility of fuzzy information retrieval systems. Expanding the fuzzy-valued concept network architecture to the Internet environment, we propose a fuzzy information retrieval method based on the network-type fuzzy-valued concept network and it can be relatively more effective information retrieval in the distributed network

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