Modeling Associative Memories Using Formal Concept Analysis

被引:3
|
作者
Kumar, Cherukuri Aswani [1 ]
Ishwarya, M. S. [1 ]
Loo, Chu Kiong [2 ]
机构
[1] VIT Univ, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
[2] Univ Malaya, Fac CS & IT, Dept Artificial Intelligence, Kuala Lumpur, Malaysia
关键词
Associative Memories; Concept Hierarchy; Concept Lattice; Formal Concept Analysis; Pattern Association; ARTIFICIAL NEURAL-NETWORKS; REPRESENTATION; KNOWLEDGE; FCANN; RULES; ANN;
D O I
10.1007/978-3-319-13153-5_11
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Associative memory is one of the primary functions of the human brain. In the literature, there are several neural networks based models that represent associative memory with the help of pattern associations. In this paper, we model the associative memory activity using Formal Concept Analysis (FCA), which is a standard technique for data and knowledge processing. In our proposal, patterns are associated with the help of object-attribute relations and the memory is represented using the formal concepts generated using FCA. We show that the extent and intent relations in the concepts help us to recall the patterns bi-directionally. Further, we model the pattern recall process for the given input even when the exact match is not found in the memory, using the concept hierarchies in the concept lattice.
引用
收藏
页码:109 / 118
页数:10
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