Factor Query Language (FQL): A Fundamental Language for the Next Generation of Intelligent Database

Xiangfu Meng (), Jing Wen, Jiasheng Shi, Zihan Li, Jinxia Zhu and Peizhuang Wang
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Xiangfu Meng: Liaoning Technical University
Jing Wen: Liaoning Technical University
Jiasheng Shi: Liaoning Technical University
Zihan Li: Liaoning Technical University
Jinxia Zhu: Liaoning Technical University
Peizhuang Wang: Liaoning Technical University

Annals of Data Science, 2022, vol. 9, issue 3, No 7, 539-554

Abstract: Abstract Factor space theory was first proposed in the 1980s with the rough set theory. After 30 years of development, factor space theory has established its completed theoretical architecture in mathematics; it has been proved very useful in causal analysis, intelligent reasoning and decision making. This paper proposes a Factor Query Language (FQL)—an SQL-like query language for operating the Factor Pedigree to make the factor space theory easily and widely used. First, the concepts associated with factor and factor space are presented. The factor pedigree which builds by knowledge increase and concept partitioning is presented; an XML specification–based storage method is also proposed for storing the factor pedigree. Next, the FQL (including FQL statements for insert, delete, update and select operations) is proposed. Two kinds of node encoding of factor pedigree strategies (interval-based encoding and prime + binary string-based encoding) are designed. They can facilitate the FQL query performance efficiently. The Factor Base Management System (FBMS) architecture and module functions are also presented.

Keywords: Factor space; Factor pedigree; Factor query language (FQL); Factor encoding; Factor base management system (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s40745-022-00391-y

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