Determination of Customer Satisfaction using Improved K-means algorithm

Zare, Hamed; Emadi, Sima

doi:10.1007/s00500-020-04988-4

Cited by 25 publications

(16 citation statements)

References 66 publications

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“…Prime number determination is done using improved Miller Rabin algorithm [12]. In the process, considering that arbitrarily generated large integers are time-consuming in prime judgment, it is necessary to filter out some relatively significant composite numbers before transmitting large integers to the degree of prime judgment [13,14].…”

Section: Prime Judgmentmentioning

confidence: 99%

Hybrid Encryption Scheme for Hospital Financial Data Based on Noekeon Algorithm

Yao

2021

Security and Communication Networks

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The previous encryption methods of hospital financial data have the problem of overburden. Therefore, a research study on hybrid encryption of hospital financial data based on Noekeon algorithm is proposed. From the basic principles of the Noekeon algorithm and the application and implementation of the Noekeon algorithm, a hybrid encryption scheme for hospital financial data based on the Noekeon algorithm is designed. In order to improve the security of the encryption system, the RSA algorithm is used to encrypt the encrypted content twice. The hybrid algorithm realizes the hybrid encryption of the hospital's financial data. Finally, a hybrid encryption system for hospital financial data based on Noekeon algorithm is designed. Experimental results show that this method has a higher success rate and better comprehensive performance. It not only improves the encryption efficiency of hospital financial data but also enhances the security of hospital financial data, which has greater application value.

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Section: Prime Judgmentmentioning

confidence: 99%

Hybrid Encryption Scheme for Hospital Financial Data Based on Noekeon Algorithm

Yao

2021

Security and Communication Networks

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“…Only on this basis, product development decisions and recommendation strategies can better meet the needs of users and contribute to consumer satisfaction (Wijekoon et al, 2021). Clustering technologies such as k-means algorithm (Zare & Emadi, 2020), association rules (Hang et al, 2005), content-based and collaborative filtering technologies (Jung et al, 2003) have been proved to be effective user preference identification methods. Internet, the availability of consumer behavior data supports relevant studies on user preference modeling (A. N. Wang et al, 2020).…”

Section: User Preference Identification and Product Improvementmentioning

confidence: 99%

“…Next, the k-means method was applied to user segmentation according to the importance vectors, and user groups with different degree of emphasis on product attributes can be subdivided through user clustering. The k-means is a classical clustering algorithm based on Euclidean distance (Zare & Emadi, 2020). It firstly selects 𝑘 samples as the initial center points.…”

Section: User Segmentation Based On Their Emphasis On Product Attributesmentioning

confidence: 99%

Research on personalized user-centered product improvement based on sentiment mining of online reviews and competitor analysis

Liu,

2022

Preprint

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Online reviews contain a wealth of information about product performance and user sentiment, which can effectively assist manufacturers to make production decisions. Taking abundant online reviews as data, this study mined product attributes and consumer sentiments to analyze users' personalized preferences and the performance of competitive products, and proposed personalized user-centered product improvement strategies for differentiated markets. Specifically, the word2vec technology and the LSTM neural network were applied to develop the sentiment mining method that was suitable for specific product domain, through which the explicit emotional information was extracted from product reviews and the missing emotional information was also predicted combined with the overall sentiment of the review text and the attitude of other consumers. On this basis, the k-means method was applied in this model firstly to segment the users according to their emphasis on product attributes. Then, a preference identification model that describes the relative importance of product attributes was designed according to the utility function and KANO theory, so as to measure consumers’ various preferences of each user group. Finally, combined with the relative performance of product attributes, the traditional IPA model was optimized to determine the improvement priority of attributes for different user groups to meet user preferences in a differentiated way. These work helps enrich the relevant theories and methods of sentiment mining and provides practical guidance for user-centered product improvement.

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“…Penelitian ini menerapkan algoritma K-Means [7] untuk mengelompokkan data ke dalam blok yang berbeda. Langkah-langkah yang diambil adalah sebagai berikut [18]…”

Section: Metode Penelitianunclassified

Algoritma K-Means untuk Mengukur Kepuasan Mahasiswa Menggunakan E-Learning

Pawening¹

2021

J. Technol. Inform.

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Penelitian ini bertujuan untuk mengukur kepuasan mahasiswa terhadap pembelajaran daring di Fakultas Teknik Universitas Nurul Jadid. Pandemi COVID-19 mengakibatkan disrupsi atau perubahan besar dalam proses pembelajaran. Fakultas Teknik Universitas Nurul Jadid. Pembelajaran yang dilakukan secara daring memberikan dampak perubahan perilaku dan juga cara mengajar. Hal ini juga berdampak pada tingkat efektifitas dan kepuasan mahasiswa dalam proses pembelajaran. Penelitian ini menggunakan metode deskriptif kualitatif menggunakan K-Means Clustering. Hasil penelititian menunjukkan derajat kepuasan mahasiswa dalam proses belajar mengajar mengalami peningkatan namun tidak signifikan. Hal ini ditunjukkan dengan prosentase respon mahasiswa terhadap penyelenggaraan pembelajaran daring sebesar 80%. Selebihnya menyatakan cukup puas, dan 7% menyatakan kurang puas dan tidak puas.

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Determination of Customer Satisfaction using Improved K-means algorithm

Cited by 25 publications

References 66 publications

Hybrid Encryption Scheme for Hospital Financial Data Based on Noekeon Algorithm

Hybrid Encryption Scheme for Hospital Financial Data Based on Noekeon Algorithm

Research on personalized user-centered product improvement based on sentiment mining of online reviews and competitor analysis

Algoritma K-Means untuk Mengukur Kepuasan Mahasiswa Menggunakan E-Learning

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