Ranking products with IF-based sentiment word framework and TODIM method

Kybernetes ◽  
2019 ◽  
Vol 48 (5) ◽  
pp. 990-1010 ◽  
Author(s):  
Chong Wu ◽  
Dong Zhang
Keyword(s):  
Decision Making ◽  
Online Reviews ◽  
Multiple Attribute Decision Making ◽  
Weighted Averaging ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Sentiment Score ◽  
Use Of Knowledge ◽  
Sentiment Word

Purpose The purpose of this paper is to rank products by combining sentiment analysis (SA) and multiple attribute decision-making (MADM). Design/methodology/approach This research constructs intuitionistic fuzzy (IF)-based sentiment word framework and corresponding computation rules, which aim to calculate the sentiment score of each sentiment phase. Based on intuitionistic fuzzy weighted averaging operator, the authors aggregate the overall performance of each feature for different products. Then, the MADM method can be used, TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) in this paper, to rank product through online reviews. Findings The results of the research show the superiority and applicability of proposed method in ranking products with online reviews. Originality/value This paper proposes IF-based sentiment word framework and corresponding computation rules, which is a novel idea to express both the sentiment orientations (positive, negative and neutral) and emotional intensities. In addition, this research makes full use of knowledge from both experts and online reviewers. Further, attention degree of each feature is considered in the process of calculating weight of different features, which is rarely seen in current studies. This paper makes full use of SA, fuzzy control theory and MADM theory to handle vague information (online comments) and rank alternative products, which can promote future perspectives and developments.

scholarly journals Generalized Linguistic Hesitant Intuitionistic Fuzzy Hybrid Aggregation Operators

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Yang ◽  
Jiarong Shi ◽  
Yongfeng Pang
Keyword(s):  
Decision Making ◽  
Geometric Mean ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
New Method ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Special Cases

Some hybrid aggregation operators have been developed based on linguistic hesitant intuitionistic fuzzy information. The generalized linguistic hesitant intuitionistic fuzzy hybrid weighted averaging (GLHIFHWA) operator and the generalized linguistic hesitant intuitionistic fuzzy hybrid geometric mean (GLHIFHGM) operator are defined. Some special cases of the new aggregation operators are studied and many existing aggregation operators are special cases of the new operators. A new multiple attribute decision making method based on the new aggregation operators is proposed and a practical numerical example is presented to illustrate the feasibility and practical advantages of the new method.

scholarly journals Algorithms Based on COPRAS and Aggregation Operators with New Information Measures for Possibility Intuitionistic Fuzzy Soft Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Harish Garg ◽  
Rishu Arora
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Soft Decision ◽  
Information Measures ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute

The objective of this paper is to present novel algorithms for solving the multiple attribute decision-making problems under the possibility intuitionistic fuzzy soft set (PIFSS) information. The prominent characteristics of the PIFSS are that it considers the membership and nonmembership degrees of each object during evaluation and their corresponding possibility degree. Keeping these features, this paper presents some new operation laws, score function, and comparison laws between the pairs of the PIFSSs. Further, we define COmplex PRoportional ASsessment (COPRAS) and weighted averaging and geometric aggregation operators to aggregate the PIFSS information into a single one. Later, we develop two algorithms based on COPRAS and aggregation operators to solve decision-making problems. In these approaches, the experts and the weights of the parameters are determined with the help of entropy and the distance measure to remove the ambiguity in the information. Finally, a numerical example is given to demonstrate the presented approaches.

An Approach to Multiple Attribute Decision Making with Triangular Intuitionistic Fuzzy Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7285-7288
Author(s):  
Jinping Chen
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Construction Projects ◽  
Multiple Attribute Decision Making ◽  
Intuitionistic Fuzzy Sets ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Multiple Attribute

The aim of this paper is to investigate the multiple attribute decision making problems with triangular intuitionistic fuzzy information. Some operational laws of triangular intuitionistic fuzzy sets, score functions of triangular intuitionistic fuzzy sets are introduced. Based on these operational laws, some Einstein aggregation operators, including triangular intuitionistic fuzzy Einstein weighted averaging (TIFEWA) operator, triangular intuitionistic fuzzy Einstein ordered weighted averaging (TIFEOWA) operator and triangular intuitionistic fuzzy Einstein hybrid aggregation (TIFEHA) operator, are proposed. An approach to multiple attribute decision making with triangular intuitionistic fuzzy information is developed based on the TIFEWA operator. Finally, an illustrative example for evaluating the construction projects quality with triangular intuitionistic fuzzy information is given to verify the developed approach.

Some Improved Linguistic Intuitionistic Fuzzy Aggregation Operators and Their Applications to Multiple-Attribute Decision Making

2017 ◽  
Vol 16 (03) ◽  
pp. 817-850 ◽  
Author(s):  
Peide Liu ◽  
Peng Wang
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Multi Attribute Decision Making

Linguistic intuitionistic fuzzy numbers (LIFNs) is a new concept in describing the intuitionistic fuzzy information, which membership and non-membership are expressed by linguistic terms, so it can more easily express the fuzzy information, and some research results on LIFNs have been achieved. However, in the existing researches, some linguistic intuitionistic fuzzy aggregation operators are based on the traditional operational rules, and they have some drawbacks for multi-attribute decision making (MADM) in the practical application. In order to overcome these problems, in this paper, we proposed some improved operational rules based on LIFNs and verified their some properties. Then we developed some aggregation operators to fuse the decision information represented by LIFNs, including the improved linguistic intuitionistic fuzzy weighted averaging (ILIFWA) operator and the improved linguistic intuitionistic fuzzy weighted power average (ILIFWPA) operator. Further, we proved their some desirable properties. Based on the ILIFWA operator and the ILIFWPA operator, we presented some new methods to deal with the multi-attribute group decision making (MAGDM) problems under the linguistic intuitionistic fuzzy environment. Finally, we used some practical examples to illustrate the validity and feasibility of the proposed methods by comparing with other methods.

scholarly journals Lexicographic Orders of Intuitionistic Fuzzy Values and Their Relationships

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 166 ◽  
Author(s):  
Feng Feng ◽  
Meiqi Liang ◽  
Hamido Fujita ◽  
Ronald Yager ◽  
Xiaoyan Liu
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Scalar Product ◽  
Multiple Attribute Decision Making ◽  
Benchmark Problem ◽  
Score Functions ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Risk Investment ◽  
Membership Score

Intuitionistic fuzzy multiple attribute decision making deals with the issue of ranking alternatives based on the decision information quantified in terms of intuitionistic fuzzy values. Lexicographic orders can serve as efficient and indispensable tools for comparing intuitionistic fuzzy values. This paper introduces a number of lexicographic orders by means of several measures such as the membership, non-membership, score, accuracy and expectation score functions. Some equivalent characterizations and illustrative examples are provided, from which the relationships among these lexicographic orders are ascertained. We also propose three different compatible properties of preorders with respect to the algebraic sum and scalar product operations of intuitionistic fuzzy values, and apply them to the investigation of compatible properties of various lexicographic orders. In addition, a benchmark problem regarding risk investment is further explored to give a comparative analysis of different lexicographic orders and highlight the practical value of the obtained results for solving real-world decision-making problems.

scholarly journals Research on the Evaluation Model of Urban Tourism Management Efficiency with Uncertain Linguistic Information

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Song-Mao Wang ◽  
Liang-Yan Fang ◽  
Feng Deng
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Multiple Attribute Decision Making ◽  
Urban Tourism ◽  
Weighted Averaging ◽  
Linguistic Information ◽  
Management Efficiency ◽  
Tourism Management ◽  
Proposed Model ◽  
Multiple Attribute

We investigate the multiple attribute decision making problems for evaluating the urban tourism management efficiency with uncertain linguistic information. We utilize the uncertain linguistic weighted averaging (ULWA) operator to aggregate the uncertain linguistic information corresponding to each alternative and get the overall value of the alternatives and, then rank the alternatives and select the most desirable one(s). Finally, a numerical example for evaluating the urban tourism management efficiency with uncertain linguistic information is used to illustrate the proposed model.

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