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Found 6 papers, 0 papers with code
DBGSA: A Novel Data Adaptive Bregman Clustering Algorithm
In this paper, we address these problems by proposing a data-driven Bregman divergence parameter optimization clustering algorithm (DBGSA), which combines the Universal Gravitational Algorithm to bring similar points closer in the dataset.
A rule-general abductive learning by rough sets
By transforming the target concept and sub-concepts of rules into information tables, rough set theory is used to solve the acquisition of domain knowledge and the correction, reduction and generation of rules at a lower cost.
A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System
Currently, matrix decomposition is one of the most widely used collaborative filtering algorithms by using factor decomposition to effectively deal with large-scale rating matrix.
RNNCTPs: A Neural Symbolic Reasoning Method Using Dynamic Knowledge Partitioning Technology
Although traditional symbolic reasoning methods are highly interpretable, their application in knowledge graph link prediction is limited due to their low computational efficiency.
Neural Theorem Provers Delineating Search Area Using RNN
Although traditional symbolic reasoning methods are highly interpretable, their application in knowledge graphs link prediction has been limited due to their computational inefficiency.
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization
In this paper, an algorithm for nonnegative matrix approximation is proposed.
