The phrase "a hidden relation" is correct and usable in written English.
It can be used when discussing connections or associations that are not immediately obvious or visible.
Example: "In her research, she uncovered a hidden relation between the two variables that had previously gone unnoticed."
Alternatives: "an obscure connection" or "a concealed link".
The proposed method firstly computes multi-view convolutional features to achieve improved object representation, then analyses the similarities between objects by operating over multiple hidden relation types (modalities), and finally fine-tunes the entire model variables via back-propagating a ranking loss to the convolutional layers.
Discovering hidden relations is a daunting challenge specifically when multiple entities and relationships are interconnected at different levels.
Select a new center or mode for every cluster and compare it with the previous value of centre or mode; if the values are different, continue with step 2. Association rule mining [28] is a very popular data mining technique that extracts interesting and hidden relations between various attributes in a large data set.
Secondly, in our approach, a graph-based methodology based Semantic MEDLINE is presented to mine hidden relations between biomedical entities.
Word vector is more suitable for extracting hidden relations.
To improve model interpretability and generalization, sparsity is imposed over these hidden relations.
Techniques from soft computing are preferable than statistics because of their ability for noise rejection and learning hidden relations between parameters.
Due to the knowledge and experience intensive nature of fault diagnosis, the diagnostic result very much depends on the preference of the decision makers on the hidden relations between possible faults and the presented symptom.
Usage of data-driven prognostics has many advantages such as no system knowledge is required, it is fast and easy to implement, the algorithm can be tuned to be used for another system, and hidden relations about the system behavior may be learned.
This approach is useful to establish hidden relations between biomedical concepts from literature compare to the commonly used co-occurrence-based methods [23], [24].
