Aspect based sentiment analysis and smart classification in uncertain feedback pool

Kumar, V. Vinoth; Raghunath, K. M. Karthick; Muthukumaran, V.; Joseph, Rose Bindu; Beschi, I. S.; Uday, Akshay K.

doi:10.1007/s13198-021-01379-2

Cited by 24 publications

(12 citation statements)

References 9 publications

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“…The machine learning model based on a neuro-information system provides more accurate results for an individual (Kumar et al. , 2022).…”

Section: Discussionmentioning

confidence: 99%

“…, 2022). In today’s globalized world, most multinational corporations are implementing neuro-marketing (Kumar et al. , 2022) to measure their customers’ physiological and neural signals and glean insights to predict and manipulate their behavior through targeted advertising campaigns, pricing policies, product development and other marketing activities (Turel and Bechara, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…This issue can be addressed by employing an automated sentiment analysis that can easily predict online shopping behavior. Sentiment analysis based on neuroscience information accurately predicts purchase behavior of both potential buyers and existing customers (Kumar et al. , 2022).…”

Section: Discussionmentioning

confidence: 99%

“…The convolution kernel matches the image pixel from the input images. A Haar feature is similar to the convolution kernel which is used to match the feature in the input images (Kumar et al. , 2022).…”

Section: Introductionmentioning

confidence: 99%

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Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions

Srivastava

Bag²

2023

BIJ

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PurposeData-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.Design/methodology/approachThe study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.FindingsAn extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.Practical implicationsNeuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.Originality/valueThe uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.

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“…The machine learning model based on a neuro-information system provides more accurate results for an individual (Kumar et al. , 2022).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions

Srivastava

Bag²

2023

BIJ

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“…When nodes lose power, WSN partitions and their network cease to communicate, which is a common concern and is defined as a hot-spot scenario where the WSN becomes disconnected due to the node's energy depletion [14]. To resolve this kind of issue, experts employ two distinct approaches.…”

Section: Related Workmentioning

confidence: 99%

Incorporation of Energy Efficient Computational Strategies for Clustering and Routing in Heterogeneous Networks of Smart City

et al. 2022

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For decision-making and governance, smart cities depend on tracking data collected via a substantial percentage of wireless sensing nodes. However, several limitations affect Wireless Sensor Network (WSN)-based Internet of Things (IoT) services, such as low battery life, recurrent connectivity problems due to multi-hop connections, and a limited channel capacity. Furthermore, in many systems, clustering and routing are handled independently, which prevents the adaptation of effective strategies for optimal energy usage and prolonged network lifespan. This research gathers data from heterogeneous IoT nodes linked via WSN and distributed across a smart infrastructure. There are two interrelated problems to be addressed with respect to energy efficiency computations: clustering and routing. We provide a new clustering strategy through which efficient routing of critical and regular data is handled. As a result, both clustering and routing have been significantly strengthened, which balances the communication load across different sectors of the smart infrastructure network. Minkowski distance and ranking strategy are used for routing and selecting cluster heads, respectively. Deterministic distributed–time division multiple access (DD-TDMA) scheduling is employed to balance the communication load across the network. The experimental results show that the proposed work outperforms some of the popular cluster-based routing strategies.

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Aspect-Based Opinion Mining Framework for Product Rating Embedded with Fuzzy Decision

Srivastava

Singh²,

Kumar

2023

Lecture Notes in Electrical Engineering

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Aspect based sentiment analysis and smart classification in uncertain feedback pool

Cited by 24 publications

References 9 publications

Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions

Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions

Incorporation of Energy Efficient Computational Strategies for Clustering and Routing in Heterogeneous Networks of Smart City

Aspect-Based Opinion Mining Framework for Product Rating Embedded with Fuzzy Decision

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