Multiple affective attribute classification of online customer product reviews: A heuristic deep learning method for supporting Kansei engineering

Wang, Wai Ming; Wang, J. W.; Li, Zhi; Tian, Zonggui; Tsui, Eric

doi:10.1016/j.engappai.2019.05.015

Cited by 68 publications

(36 citation statements)

References 32 publications

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“…This research uses the Kansei Engineering System. This method can translate the emotional needs of consumers into product parameters so that products are made following consumer desires [11] [12]. This method can be applied to designing a product and also a working system.…”

Section: Methodsmentioning

confidence: 99%

“…The method used is Kansei Engineering. This method can translate user needs into a design parameter [11] [12] so that the design is made or by the needs of its users [13]. This method can also be used to solve physical facility problems such as facilities of inpatient hospital [14], elementary school desk and chairs [15], dining stalls [16], and supermarket trolleys [17].…”

Section: Introductionmentioning

confidence: 99%

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Ergonomic Work System Design Using Kansei Engineering Approach

Purnomo

Lestari

Kisanjani

2020

Sinergi

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Work fatigue is a problem that most often arises in the workplace and can affect work productivity. That problem also occurs at PT ASA Yogyakarta, many workers who complain of aches in the upper muscles and waist at work. Based on this, the research aims to design an ergonomic work system on the sewing production floor of PT. ASA Yogyakarta. The design of the work system is done to fix the problems done by workers so that it is expected to increase productivity. The method used is Kansei Engineering. The results of this study indicate that the proposed work system design meets the desires of workers with Stuart-Maxwell values testing marginal homogeneity of Z> 0.05. Work system designs made include sewing chairs and tables adjusted in size to worker anthropometry, approved backrests on chairs, lighting lamps replaced with LED lights, plug lamps on sewing machines, and plug bulkheads as sound dampers.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ergonomic Work System Design Using Kansei Engineering Approach

Purnomo

Lestari

Kisanjani

2020

Sinergi

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“…Initially, oral interviews and questionnaires were commonly used. Later, researchers began collecting electroencephalography signals, 24 used eye‐tracking technology, 25 and mined online comments 26 . At this stage, researchers need to ensure the validity and accuracy of the data to reduce errors in the subsequent research steps.…”

Section: Literature Reviewmentioning

confidence: 99%

Product color emotional design based on a convolutional neural network and search neural network

Ding

Cheng

Zhang

et al. 2021

Color Research & Application

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Due to the growing trend of social manufacturing, product design has focused on meeting the emotional needs of users. As a product attribute, color plays an important role in meeting these needs. Therefore, product color emotional design has attracted the attention of researchers. However, a user's perception of the emotional image of product color is highly complex, and it is difficult to define this perception accurately. To this end, based on the theoretical framework of Kansei engineering, this study proposes a product color emotional design method based on a convolutional neural network and a search neural network. First, we implement a semantic differential experiment to ascertain the user's color image. Then we use a convolutional neural network to establish a complex association model between the product color and the user's emotional imagery. Based on this model, the search neural network is used to search and generate the product color design scheme that meets the target image. Finally, a product color design system applicable to practical design problems is developed. An example of the design of a home service robot demonstrates that the proposed method and system provides accurate product color design solutions that meet the needs of the user's emotional image and can be used to develop practical large‐scale applications of product color emotional design theory and methods.

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“…Serta dapat memberikan gambaran atau prediksi ke depan bagaimana tampilan smartphone yang dapat dikembangkan kedepannya [8]. Untuk penerapanya, pertama perlu ditentukan jenis aplikasi/website yang akan dibuat, selanjutnya mengumpulkan Kansei Word berdasarkan kebutuhan, dan dilanjutkan dengan survei pengguna agar dapat diolah dan menghasilkan data yang dapat diubah menjadi sebuah desain aplikasi yang sesuai [9].…”

Section: A Rumusan Masalahunclassified

Penerapan Kansei Engineering dalam Perbandingan Desain Aplikasi Mobile Marketplace di Indonesia

Vilano¹,

Budi²

2020

JuTISI

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The company's application design is very important because it displays the company's image and to attract more users to purchase/utilize the application. This research applies Kansei Engineering Method to analyze the emotion or feelings of the user towards the design of a mobile application interface. Six Kansei Words and three specimens are utilised in this research, where Kansei words are selected from words related to user experience. The participants of this research consist of 54 students from Maranatha Christian University. Participants’ responses are studied using multivariate statistical analysis (e.g., Coefficient Correlation Analysis, Principal Component Analysis, and Factor Analysis). This study explores the emotional factors that occur in designing an application. This analysis shows that there are some major factors that greatly influence the design of a mobile application interface.

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Multiple affective attribute classification of online customer product reviews: A heuristic deep learning method for supporting Kansei engineering

Cited by 68 publications

References 32 publications

Ergonomic Work System Design Using Kansei Engineering Approach

Ergonomic Work System Design Using Kansei Engineering Approach

Product color emotional design based on a convolutional neural network and search neural network

Penerapan Kansei Engineering dalam Perbandingan Desain Aplikasi Mobile Marketplace di Indonesia

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