Ranking products through online reviews considering the mass assignment of features based on BERT and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si22.svg" display="inline" id="d1e1760"><mml:mi>q</mml:mi></mml:math>-rung orthopair fuzzy set theory

Yin, Songyi; Wang, Yu; Shafiee, Sara

doi:10.1016/j.eswa.2022.119142

Cited by 20 publications

(3 citation statements)

References 46 publications

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“…Liu et al [17] manually extended the medical review corpus using a lexicon-based SA approach in the problem of doctor selection. By contrast, deep learning models, such as BERT [18], LSTM [6], RoBERTa [9], and Bidirectional Long and Short-Term Memory (BiL-STM) [19], show strong language understanding and transfer learning, including high accuracy in SA. BERT-BiLSTM [20] is an improved algorithm that fuses Transformer Bidirectional Encoded Representation (BERT) and BiLSTM.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Online review–driven Product Recommendation Ranking Considering Interactions Among Features and Consumers’ Psychology

Liu,

Li,

Chin

2024

Preprint

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In the digital economy, online reviews serve as valuable and real-time feedback for consumers, making them a crucial source of information for product selection. We propose a product recommendation ranking method based on sentiment analysis of online reviews to address information overload and support informed purchase decisions. The proposed model considers the interdependencies among product features and fully simulates the psychological state of consumers before and after purchasing products. First, online reviews of products are mined and preprocessed. Natural language processing techniques are employed to extract product features and perform aspect-based sentiment analysis. The results are transformed into an evaluation matrix of the probabilistic linguistic term sets (PLTSs). Then, we propose a 2-additive fuzzy measures recognition model based on multi-dimensional feature attention information to effectively identify redundant, independent, and complementary interactions among product features. Subsequently, the fuzzy weight and the proposed possibility comprehensive discrepancy measures are applied to the interactive multi-criteria decision-making based on CPT-TODIM (Cumulative Prospect Theory TODIM) method to rank the recommended priorities of alternative products. The feasibility of the proposed method is validated through a case study of smart sweeping robot products from Jingdong Mall, followed by the investigation of the impact of various psychological behaviours that influence purchase decisions on the recommendation ranking based on stochastic multi-criteria acceptability analysis (SMAA). Finally, a comparative analysis is conducted to demonstrate the advantages and effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Online review–driven Product Recommendation Ranking Considering Interactions Among Features and Consumers’ Psychology

Liu,

Li,

Chin

2024

Preprint

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“…These distinctive features have attracted significant attention, leading to extensive research conducted by renowned scholars and practical applications across a wide range of domains. For example, By employing transformers and q -ROFS theory, an innovative approach for ranking products that took into account the mass assignment of features was presented by Yin et al ( 2023 ). Then, Fetanat and Tayebi ( 2023 ) created the q -ROFS based MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis), a unique hybrid decision support system.…”

Section: Introductionmentioning

confidence: 99%

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

Mahboob,

Ullah,

Ovais

et al. 2024

Front. Artif. Intell.

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The impact of artificial intelligence (AI) in education can be viewed as a multi-attribute group decision-making (MAGDM) problem, in which several stakeholders evaluate the advantages and disadvantages of AI applications in educational settings according to distinct preferences and criteria. A MAGDM framework can assist in providing transparent and logical recommendations for implementing AI in education by methodically analyzing the trade-offs and conflicts among many components, including ethical, social, pedagogical, and technical concerns. A novel development in fuzzy set theory is the 2-tuple linguistic q-rung orthopair fuzzy set (2TLq-ROFS), which is not only a generalized form but also can integrate decision-makers quantitative evaluation ideas and qualitative evaluation information. The 2TLq-ROF Schweizer-Sklar weighted power average operator (2TLq-ROFSSWPA) and the 2TLq-ROF Schweizer-Sklar weighted power geometric (2TLq-ROFSSWPG) operator are two of the aggregation operators we create in this article. We also investigate some of the unique instances and features of the proposed operators. Next, a new Entropy model is built based on 2TLq-ROFS, which may exploit the preferences of the decision-makers to obtain the ideal objective weights for attributes. Next, we extend the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique to the 2TLq-ROF version, which provides decision-makers with a greater space to represent their decisions, while also accounting for the uncertainty inherent in human cognition. Finally, a case study of how artificial intelligence has impacted education is given to show the applicability and value of the established methodology. A comparative study is carried out to examine the benefits and improvements of the developed approach.

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“…Qin, Xu, and Zheng [34] established an axiomatic framework for the fuzzy entropy and overall entropy of T2FSs and proposed a decision method based on type-2 fuzzy entropy, which was applied to the selection of cold medicine through online reviews. Yin, Wang, and Shafiee [35] proposed a product ranking method based on bidirectional encoder representation considering the mass assignment of features. In this method, a transformer was used to identify the sentiment orientation and product features, and the q-rung orthopair fuzzy numbers were aggregated by the q-rung orthopair fuzzy generalized weighted Heronian mean operator to rank the products.…”

Section: Introductionmentioning

confidence: 99%

Product Selection Considering Multiple Consumers’ Expectations and Online Reviews: A Method Based on Intuitionistic Fuzzy Soft Sets and TODIM

Cao,

Zheng,

2023

Mathematics

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Large amounts of online reviews from e-commerce sites and social media platforms can help potential consumers to better understand products and play an important part in assisting potential consumers in making purchase decisions. Moreover, while multiple consumers purchase the same product, the index parameters of the product that are of concern among them are usually different, i.e., they have different expectations for the product. Therefore, the question of how to effectively analyze online product reviews and consider multiple consumers’ expectations to select products is an important issue that needs to be addressed. The objective of this study is to propose a product selection method based on intuitionistic fuzzy soft sets and TODIM. Firstly, the online reviews are extracted by the web crawler and are pretreated. Next, the sentiment orientations of each online review concerning product index parameters are recognized using the dictionary-based sentiment analysis algorithm. Then, the evaluation values of sentiment orientations for product index parameters are firstly expressed by intuitionistic fuzzy numbers and are then transformed into intuitionistic fuzzy soft sets. Further, the alternative product set is obtained according to the uni-int decision function and multiple consumers’ expectations, and we then rank the alternative products using the TODIM method. Finally, a case study is provided to illustrate the validity and feasibility of the proposed method.

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Ranking products through online reviews considering the mass assignment of features based on BERT and q-rung orthopair fuzzy set theory

Cited by 20 publications

References 46 publications

RETRACTED: Online review–driven Product Recommendation Ranking Considering Interactions Among Features and Consumers’ Psychology

RETRACTED: Online review–driven Product Recommendation Ranking Considering Interactions Among Features and Consumers’ Psychology

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

Product Selection Considering Multiple Consumers’ Expectations and Online Reviews: A Method Based on Intuitionistic Fuzzy Soft Sets and TODIM

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