Humberto Bustince

TL;DR: A new data flow is proposed that takes advantage of the sorting and merging phases of MapReduce to group duplicated/conflicting rules and avoids an exhaustive search over the rule base, and removes the bottleneck caused by the execution of a single reducer by supporting as many reducers as needed.

TL;DR: This work addresses L-fuzzy context sequences where one or more values are missing and proposes new methods to tackle the problem and uses the study of tendencies to analyse relationships between the objects and the attributes of L- fuzzy contexts and to replace the absent values taking into account the behaviour of the sequence.

TL;DR: In this paper , the Sugeno integral is extended to work with interval-valued data and the authors use this integral to aggregate intervalvalued data in two different settings: first, they study the use of intervals in a brain-computer interface, and secondly they study how to construct intervalvalued relationships in a social network, and how to aggregate their information.

TL;DR: A new unsupervised approach to perform tumor delineation in PET images using Atanassov’s intuitionistic fuzzy sets (A-IFSs) and restricted dissimilarity functions is introduced.

TL;DR: In this paper, the problem of measuring the degree of inclusion and equivalence measure for Atanassov intuitionistic fuzzy setting is considered and it is proposed by using the partial or linear order on AtanASSov intuitionist fuzzy setting.