Fuzzy Based Approach to Develop Hybrid Ranking Function for Efficient Information Retrieval

2015 ◽  
pp. 471-479
Author(s):  
Ashish Saini ◽  
Yogesh Gupta ◽  
Ajay K. Saxena
Keyword(s):  
Information Retrieval ◽  
Ranking Function ◽  
Efficient Information

scholarly journals Thesaurofacet - the information retrieval language of the 21st century

2016 ◽  
pp. 73-81
Author(s):  
Eduard Sukiasyan
Keyword(s):  
Information Retrieval ◽  
Retrieval Systems ◽  
Efficient Information ◽  
Retrieval Language

The term of “thesaurofest” is scrutinized; the characteristics of the system, the technologies of efficient information retrieval are analyzed. Prospects for retrieval systems modernization are discussed.

Genetic-Fuzzy Programming Based Linkage Rule Miner (GFPLR-Miner) for Entity Linking in Semantic Web

2021 ◽  
pp. 447-481
Author(s):  
Amit Singh ◽  
Aditi Sharan
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Semantic Web ◽  
Real World ◽  
Fuzzy Programming ◽  
Data Sources ◽  
Fuzzy Approach ◽  
Entity Linking ◽  
Efficient Information ◽  
Domain Independent

This article describes how semantic web data sources follow linked data principles to facilitate efficient information retrieval and knowledge sharing. These data sources may provide complementary, overlapping or contradicting information. In order to integrate these data sources, the authors perform entity linking. Entity linking is an important task of identifying and linking entities across data sources that refer to the same real-world entities. In this work, they have proposed a genetic fuzzy approach to learn linkage rules for entity linking. This method is domain independent, automatic and scalable. Their approach uses fuzzy logic to adapt mutation and crossover rates of genetic programming to ensure guided convergence. The authors' experimental evaluation demonstrates that our approach is competitive and make significant improvements over state of the art methods.

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