Web Personalization Model Using Modified S3VM Algorithm For developing Recommendation Process

Rajawat, Anand Singh; Upadhyay, Akhilesh R.

doi:10.1109/idea49133.2020.9170701

Cited by 23 publications

(5 citation statements)

References 15 publications

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“…Applying our approach reduces the web application problem for classifying and improves big data accuracy; Big data is quite common nowadays. The results of this research are essential for the training of datasets for neural network-S3VM [ 32 ] algorithm-based classification problems.…”

Section: Proposed Methodologymentioning

confidence: 99%

Dark Web Data Classification Using Neural Network

Rajawat

Bedi

Goyal

et al. 2022

Computational Intelligence and Neuroscience

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There are several issues associated with Dark Web Structural Patterns mining (including many redundant and irrelevant information), which increases the numerous types of cybercrime like illegal trade, forums, terrorist activity, and illegal online shopping. Understanding online criminal behavior is challenging because the data is available in a vast amount. To require an approach for learning the criminal behavior to check the recent request for improving the labeled data as a user profiling, Dark Web Structural Patterns mining in the case of multidimensional data sets gives uncertain results. Uncertain classification results cause a problem of not being able to predict user behavior. Since data of multidimensional nature has feature mixes, it has an adverse influence on classification. The data associated with Dark Web inundation has restricted us from giving the appropriate solution according to the need. In the research design, a Fusion NN (Neural network)-S3VM for Criminal Network activity prediction model is proposed based on the neural network; NN- S3VM can improve the prediction.

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Section: Proposed Methodologymentioning

confidence: 99%

Dark Web Data Classification Using Neural Network

Rajawat

Bedi

Goyal

et al. 2022

Computational Intelligence and Neuroscience

Self Cite

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Section: Pendahuluanunclassified

“…Dalam penelitian sebelumnya, telah dilakukan beberapa studi dan pengembangan terkait dengan penerapan teknologi artificial intelligence dalam bidang industri makanan dan minuman [5], [6]. Beberapa penelitian telah menunjukkan bahwa personalisasi dapat digunakan untuk mempersonalisasi perilaku pengguna berdasarkan data penggunaan menggunakan teknologi artificial intelligence [5], [6]. Selain itu, penelitian terdahulu juga telah mengidentifikasi faktorfaktor yang mempengaruhi hasil rekomendasi cafe, sehingga rekomendasi yang diberikan sesuai dengan kebutuhan dan preferensi pengguna [7], [8], [9].…”

Section: Pendahuluanunclassified

Personalisasi Otomatis Aplikasi Caca (Cari Cafe) Berbasis Artificial Intelligence

Pusriwijayanti,

Prasetiadi,

Chika Fransisca

2023

smartcomp

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Peningkatan produksi kopi menciptakan peluang bisnis olahan kopi, memunculkan banyak cafe. Dalam mengikuti perkembangan zaman, pengusaha perlu menggunakan teknologi terkini dengan menyediakan aplikasi reservasi cafe untuk meningkatkan kepuasan pelanggan dan bersaing di pasar yang semakin kompetitif. Penelitian sebelumnya mengenai aplikasi berbasis mobile dengan Extreme Programming yang fokus pada kepuasan pelanggan, memungkinkan pemesanan makanan lebih awal, dan memantau pesanan pelanggan melalui website. Penelitian ini membuat aplikasi CACA (Cari Cafe) yang dirancang untuk melakukan reservasi cafe dan menyediakan informasi tentang cafe-cafe pada satu aplikasi berbasis website. Dalam mencapai personalisasi otomatis, teknologi artificial intelligence seperti Optical Character Recognition (OCR), Convolutional Neural Network (CNN), dan Siamese Neural Network (SNN) digunakan.Personalisasi otomatis aplikasi CACA melibatkan pembacaan e-KTP sebagai data registrasi, pengenalan gambar wajah pengguna untuk memberikan rekomendasi cafe berdasarkan kesukaan atau kebiasaan, dan pencocokan wajah pengguna untuk verifikasi akun member. Penelitian ini berhasil mengimplementasikan OCR pada gambar e-KTP dengan bounding box di mana nilai box_loss sebesar 0.05211 dan nilai cls_loss sebesar 0.01598. Penggunaan transfer learning model VGG16 dengan fungsi aktivasi sigmoid untuk menebak 11 komponen kesukaan atau kebiasaan pengguna juga mencapai tingkat keberhasilan yang optimal. Selain itu, metode verifikasi menggunakan SNN juga memberikan hasil yang baik, dengan mencocokan foto pada gambar e-KTP dengan foto selfie dan mencapai akurasi sebesar 0.9285 dengan nilai loss 0.0170.

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“…(i) Using our approach automatically increasing efficiency and productivity [23] (ii) Automatic handling of the material (iii) Automatic increase of the security [24] and safety, reducing the stress and high risk (iv) Managing the repetitive task with creativity [25] (v) Reducing the factory traffic in complex conditions Production control is a crucial vision of Industry 4.0, [26] including improving human security [27] with Mobile Robots in Industry 4.0 [28] factories to fully connect production. Although it does not yet exist because factory systems have not been linked with a unified framework [29], this capability would allow entire production lines to be checked and optimized in different facilities [30].…”

Section: Improving Security Of Cyber-physical System Using Sdnmentioning

confidence: 99%

Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Rajawat

Bedi

Goyal

et al. 2021

Mobile Information Systems

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In this paper, the cooperation between human and robot companies plays a significant role in factories, contributing to greater productivity and efficiency. However, this development breaches established safety procedures when the workspaces are separated from the robot and the human being. These changes have been reflected in industrial robotic safety standards for the last 20 years. We have directed the expansion of a broad field of examination, which focuses on avoiding robotic humans’ effects and minimizing associated risks and consequences. The paper depicts an analysis of prominent safety systems projected and implemented in engineering robotic surroundings that contribute to safe, collective work between humans and robots. Besides, the current regulation has introduced a review and new concepts. The discussion includes multidisciplinary approaches such as estimating and evaluating human-robot collision injuries, mechanical equipment and software to minimize human-robot impacts, impact detection systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model.

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Web Personalization Model Using Modified S3VM Algorithm For developing Recommendation Process

Cited by 23 publications

References 15 publications

Dark Web Data Classification Using Neural Network

Dark Web Data Classification Using Neural Network

Personalisasi Otomatis Aplikasi Caca (Cari Cafe) Berbasis Artificial Intelligence

Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

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