Uncertain data

Gene

Multiple-criteria decision analysis

Rank (graph theory)

Probabilistic logic

Set (abstract data type)

Biochemistry

Data mining

Computer science

Mathematical optimization

Fuzzy set

Mathematics

Fuzzy logic

Transcription factor

Artificial intelligence

Dominance-based rough set approach

Combinatorics

Repressor

Chemistry

Programming language

Operator (biology)

Decision rule

Class (philosophy)

Rough set

Machine learning

Information Sciences

Given that the three-way decision (3WD) theory provides a scientific solution and reasonable semantic interpretation for solving multi-criteria decision-making (MCDM) problems, this paper presents a new 3WD model and applies it to realistic MCDM problems. Since the fuzzy neighborhood operator is effective in handling uncertain data, we first define a pair of probabilistic approximation operators via the constructed α-fuzzy neigh borhood class. Then, a 3WD model is explored in decision information systems to address the related issues in the proposed fuzzy probabilistic rough set model. In light of the above works, we establish a novel approach to classify and rank applicants for enterprise talent recruitment problems. Instead of the rule of tie-breaking, a way is given to separate applicants into three parts by combining decision attributes, and the feasibility of the approach is confirmed as well. Finally, by using a data set in the UCI database, the results of comparative and experimental analyses demonstrate that the constructed MCDM approach owns better performances in terms of effectiveness and stability.

A novel three-way decision approach in decision information systems