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You could do it with a view which concatenates 2 attributes to provide a third value, but that usually means the user cannot amend it easily--if at all.
Evaluation of Splitting Attributes to Different Blocks and Attribute Clustering Methods.
[12], which applies users' attributes to find suitable friends and establishes social relationships with strangers via a multihop trust chain.
Accessor collusion denotes that different accessors will combine their attribute components (pACs) together for decryption of a file despite the fact that they do not have enough attributes to decrypt it alone.
However, it should be pointed out that attribute discretization destroys indiscernibility relations between condition attributes and decision attributes to some extent, and it also leads to lack of information and different reduction results.
CA distributes a set of attributes to each AA and makes sure that every two AAs do not manage the same attributes.
Manufacturers sell attributes to buyers, and buyers sell them to shoppers; to complete the cycle, shoppers may also demand specific attributes from manufacturers or buyers.
(6) Collusion resistance: the dishonest users cannot combine their attributes to decrypt the encrypted data.
First of all, we need to identify the attributes of products and show a measurement method of the attributes to get a common understanding of the products by an average customer; and then, for a certain attribute selected by an individual consumer, including the attribute's level or target, we need to find a way to describe how a product meets consumer's personal preference on these selections; in other words, we need to measure a specific, individual consumer's preference.
A transfer of attributes from a debtor to an estate effectively denies the debtor use of the tax attributes to which the estate succeeds as of the start of the case.
However, when a seller overprovides attractive attributes to customers, customer delight declines, a relationship that is converse to that depicted in the Kano model.
The selection of attributes to be used as key predictors was done through hierarchical sorting of attributes and using correlation coefficient R and estimated error [epsilon] to measure similarity.
It generates a small dataset of 200 queries with 10 Boolean attributes to measure the quality of approximation algorithms comparing with the Naive approach as the naive approach is not feasible for large datasets.