A Comprehensive Survey on Multimodal Data Representation and Information Fusion Algorithms

Gaonkar, Apeksha; Chukkapalli, Yogya; Raman, Parasaran; Srikanth, Sahana; Gurugopinath, Sanjeev

doi:10.1109/conit51480.2021.9498415

Cited by 11 publications

(1 citation statement)

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“…Multimodal information fusion refers to the integration of diverse types of information to attain a more comprehensive and accurate understanding or inference (Poh & Kittler, 2010). This fusion typically involves various modalities of information, such as images, text, audio, and video, combining them to provide a richer and more comprehensive description of the data (Gaonkar et al, 2021). In the process of multimodal information fusion, fuzzy decision-making is a common technique used to handle uncertainty and fuzziness (Skalna et al, 2015).…”

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A Consumer Trust Assessment Model for Online Shopping Based on Fuzzy Fusion Decision-Making

Zhang,

Wu,

et al. 2024

Journal of Organizational and End User Computing

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With the rapid development of e-commerce, online shopping has become an indispensable part of people's daily lives. However, consumers often face trust issues during online shopping, such as product quality and seller integrity, which directly impact their shopping experience and purchasing decisions. Therefore, accurately assessing consumer trust has become a crucial task. This study first constructs a consumer trust assessment system, analyzing and selecting key factors related to consumer trust, and establishes a model for assessing consumer trust for online shopping. Subsequently, we propose an assessment method based on text mining and deep learning sentiment analysis techniques to extract consumer sentiment information from specified consumer reviews. Furthermore, through fuzzy decision-making fusion strategy, we integrate sentiment information from the dimensions of quality assurance, reliability, and responsiveness to enhance the accuracy of the assessment.

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confidence: 99%