nach oben

Erschienen in:

2024 | OriginalPaper | Buchkapitel

Empirical Analysis of Machine Learning in Enhancing the E-Business Through Structural Equation Modeling

verfasst von : P. William, Md. Rageeb, Md. Usman Roja Boina, T. R. Vijaya Lakshmi, Ashish Sharma, Nikhil Kumar Marriwala

Erschienen in: Mobile Radio Communications and 5G Networks

Verlag: Springer Nature Singapore

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The research’s main goal is to identify the crucial elements of putting machine learning techniques into practice in order to improve electronic commerce (E-business) inside the company. The data gathered will be analyzed to achieve this. In order to improve e-business and achieve sustainable development, researchers have concentrated their efforts on taking into account significant machine learning determinants that affect demand forecasting, the application of ML in purchase behavior, improving customer engagement, and support in overall cross-selling of the products. The major objective of this essay is to provide an in-depth and critical understanding of how machine learning technology may be used to enhance the performance of online businesses. As a result of the dynamic nature of the current environment in which businesses operate, enhance the value of their brands. Because of this, having an understanding of the machine learning approaches that the owners of these websites have used is more significant in this research. This is because management needs to be able to support their E-business and create the most money feasible for the owners of these websites. Because they use this kind of website approach, these commercial websites are better able to withstand the intense competition that exists in their field. In this brief message, we present these cutting-edge websites that make use of deep learning-driven machine learning and artificial intelligence. These websites are dynamic and cutting-edge at the same time.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Experimental Analysis of Emotion Recognition in Voice Using MFCC and Deep Neural Network

Nächstes Kapitel Integration of Secure Data Communication with Wireless Sensor Network Using Cryptographic Technique

Mullainathan S, Spiess J (2017) Machine learning: an applied econometric approach. J Econ Perspect 31(2):87–106

Kumar S (2022) Effective hedging strategy for us treasury bond portfolio using principal component analysis. Acad Account Financial Stud J 26(2):1–17MathSciNet

Xu W, Zhang Z, Gong D, Guan X (2014) Neural network model for the risk prediction in cold chain logistics. Int J Multimedia Ubiquitous Eng 9(8):111–124CrossRef

Tirunillai S, Tellis GJ (2014) Mining marketing meaning from online chatter: strategic brand analysis of big data using latent Dirichlet allocation. J Mark Res 51(4):463–479CrossRef

Zohuri B, Moghaddam M (2020) From business intelligence to artificial intelligence. J Mater Sci Manuf Res 1(1):10

Even-Dar E, Mansour Y (2003) Learning rates for Q-learning. J Mach Learn Res 1-25

Gupta V, Lehal GS (2009) A survey of text mining techniques and applications. J Emerg Technol Web Intell

Kaelbling LP, Littman ML, Moore AW (1996) Reinforcement learning: a survey. J Artif Intell Res 237–285

Lunh HP (1958) A business intelligence system. IBM J Res Develop 314–319

10.

Mustafa A, Akbar A, Sultan A (2009) Knowledge discovery using text mining: a programmable implementation on information extraction and categorization. Int J Multimedia Ubiquitous Eng

11.

Vieira FH, Lee LL (2007) A neural architecture based on the adaptive resonant theory and recurrent neural networks. Int J Comput Sci Appl 45–56

12.

Jadhav R, Shaikh A, Jawale MA, Pawar AB, William P (2022)System for identifying fake product using blockchain technology. In: 2022 7th international conference on communication and electronics systems (ICCES), pp 851–854. https://doi.org/10.1109/ICCES54183.2022.9835866

13.

William P, Shrivastava A, Chauhan H, Nagpal P, Singh P (2022)Framework for intelligent smart city deployment via artificial intelligence software networking. In: 2022 3rd international conference on intelligent engineering and management (ICIEM), pp 455–460. https://doi.org/10.1109/ICIEM54221.2022.9853119

14.

William P, Yogeesh N, Vimala S, Gite P (2022) Blockchain technology for data privacy using contract mechanism for 5G networks. In: 2022 3rd international conference on intelligent engineering and management (ICIEM), pp 461–465. https://doi.org/10.1109/ICIEM54221.2022.9853118

15.

Rawat R, Rimal YN, William P, Dahima S, Gupta S, Sakthidasan Sankaran K (2022) Malware threat affecting financial organization analysis using machine learning approach. Int J Inform Technol Web Eng (IJITWE) 17(1):1–20. https://doi.org/10.4018/IJITWE.304051

16.

William P, Pawar AB, Jawale MA, Badholia A, Verma V (2022) Energy efficient framework to implement next generation network protocol using ATM technology. Measure Sens 24:100477. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2022.100477

17.

Pawar AB, Jawale MA, William P, Chhabra GS, Rakshe DS, Korde SK, Marriwala N (2022) Implementation of blockchain technology using extended CNN for lung cancer prediction. Measure: Sens 100530. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2022.100530

18.

William P, Kiran YVU, Rana A, Gangodkar D, Khan I, Ashutosh K (2022)Design and implementation of IoT based framework for air quality sensing and monitoring. In: 2022 2nd international conference on technological advancements in computational sciences (ICTACS), pp 197–200. https://doi.org/10.1109/ICTACS56270.2022.9988646

19.

William P, Shamim M, Yeruva AR, Gangodkar D, Vashisht S, Choudhury A (2022) Deep learning based drowsiness detection and monitoring using behavioural approach. In: 2022 2nd international conference on technological advancements in computational sciences (ICTACS), pp 592–599. https://doi.org/10.1109/ICTACS56270.2022.9987728

20.

William P, Gupta A, Darwante NK, Gondkar SS, Verma A, Verma V (2022) Applications of internet of things in smart grid intelligent systems. In: 2022 international conference on augmented intelligence and sustainable systems (ICAISS), Trichy, India, pp 1175–1179. https://doi.org/10.1109/ICAISS55157.2022.10011092

21.

William P, Shrivastava A, Shunmuga Karpagam N, Mohanaprakash TA, Tongkachok K, Kumar K (2023) Crime analysis using computer vision approach with machine learning. In: Marriwala N, Tripathi C, Jain S, Kumar D (eds) Mobile radio communications and 5G networks. Lecture notes in networks and systems, vol 588. Springer, Singapore. https://doi.org/10.1007/978-981-19-7982-8_25

22.

William P, Darwante NK, Pawar AB, Jawale MA, Verma A (2023) Framework for implementation of smart driver assistance system using augmented reality. In: Marriwala N, Tripathi C, Jain S, Kumar D (eds) Mobile radio communications and 5G networks. Lecture notes in networks and systems, vol 588. Springer, Singapore. https://doi.org/10.1007/978-981-19-7982-8_30

23.

William P, Shrivastava A, Chauhan PS, Raja M, Ojha SB, Kumar K (2023) Natural language processing implementation for sentiment analysis on tweets. In: Marriwala N, Tripathi C, Jain S, Kumar D (eds) Mobile radio communications and 5G networks. Lecture notes in networks and systems, vol 588. Springer, Singapore. https://doi.org/10.1007/978-981-19-7982-8_26

24.

Mishra S, Choubey S, Choubey A, Yogeesh N, Durga Prasad Rao J, William P (2022)Data extraction approach using natural language processing for sentiment analysis. In: 2022 international conference on automation, computing and renewable systems (ICACRS), Pudukkottai, India, pp 970–972. https://doi.org/10.1109/ICACRS55517.2022.10029216

25.

Paithankar DN, Pabale AR, Kolhe RV, William P, Yawalkar PM (2023) Framework for implementing air quality monitoring system using LPWA-based IoT technique. Measure Sens 100709. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2023.100709

26.

Gupta K, Choubey S, Yogeesh N, William P, Kale CP (2023)Implementation of motorist weariness detection system using a conventional object recognition technique. In: 2023 international conference on intelligent data communication technologies and internet of things (IDCIoT), Bengaluru, India, pp 640–646. https://doi.org/10.1109/IDCIoT56793.2023.10052783

27.

Yawalkar PM, Paithankar DN, Pabale AR, Kolhe RV, William P (2023) Integrated identity and auditing management using blockchain mechanism. Measure: Sens 100732. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2023.100732

28.

William P et al (2023)Divination of air quality assessment using ensembling machine learning approach. In: 2023 international conference on artificial intelligence and knowledge discovery in concurrent engineering (ICECONF), Chennai, India, pp 1–10. https://doi.org/10.1109/ICECONF57129.2023.10083751

29.

Chobe PS, Padale DB, Pardeshi DB, Borawake NM, William P (2023) Deployment of framework for charging electric vehicle based on various topologies. In: 2023 international conference on artificial intelligence and knowledge discovery in concurrent engineering (ICECONF), Chennai, India, pp 1–4. https://doi.org/10.1109/ICECONF57129.2023.10084062

30.

Pardeshi DB, Chaudhari AK, Thokal P, Dighe RS, William P (2023) Framework for deployment of smart motor starter using android automation tool. In: 2023 international conference on artificial intelligence and knowledge discovery in concurrent engineering (ICECONF), Chennai, India, pp 1–6. https://doi.org/10.1109/ICECONF57129.2023.10083946

31.

Kolhe RV, William P, Yawalkar PM, Paithankar DN, Pabale AR (2023) Smart city implementation based on Internet of Things integrated with optimization technology. Measure Sens 27:100789. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2023.100789

32.

Jawale MA, William P, Pawar AB, Marriwala N (2023) Implementation of number plate detection system for vehicle registration using IOT and recognition using CNN. Measure Sens 27:100761. ISSN 2665-9174. https://doi.org/10.1016/j.measen.2023.100761

33.

William P, Lanke GR, Bordoloi D, Shrivastava A, Srivastavaa AP, Deshmukh SV (2023)Assessment of human activity recognition based on impact of feature extraction prediction accuracy. In: 2023 4th international conference on intelligent engineering and management (ICIEM), London, United Kingdom, pp 1–6. https://doi.org/10.1109/ICIEM59379.2023.10166247

34.

William P, Lanke GR, Inukollu VNR, Singh P, Shrivastava A, Kumar R (2023)Framework for design and implementation of chat support system using natural language processing. In: 2023 4th international conference on intelligent engineering and management (ICIEM), London, United Kingdom, pp 1–7. https://doi.org/10.1109/ICIEM59379.2023.10166939

35.

William P, Shrivastava A, Aswal US, Kumar I, Gupta M, Rao AK (2023)Framework for implementation of android automation tool in agro business sector. In: 2023 4th international conference on intelligent engineering and management (ICIEM), London, United Kingdom, pp 1–6. https://doi.org/10.1109/ICIEM59379.2023.10167328

36.

William P, Lanke GR, Pundir S, Kumar I, Gupta M, Shaw S (2023)Implementation of hand written based signature verification technology using deep learning approach. In: 2023 4th international conference on intelligent engineering and management (ICIEM), London, United Kingdom, pp 1–6. https://doi.org/10.1109/ICIEM59379.2023.10167195

37.

William P, Inukollu VNR, Ramasamy V, Madan P, Shrivastava A, Srivastava A (2023)Implementation of machine learning classification techniques for intrusion detection system. In: 2023 4th international conference on intelligent engineering and management (ICIEM), London, United Kingdom, pp 1–7. https://doi.org/10.1109/ICIEM59379.2023.10167390

38.

Korde SK, Rakshe DS, William P, Jawale MA, Pawar AB (2023) Experimental investigations on copper-based nanoparticles for energy storage applications. J Nano-and Electron Phys 15(3)

39.

Rakshe DS, William P, Jawale MA, Pawar AB, Korde SK, Deshpande N (2023) Synthesis and characterization of graphene based nanomaterials for energy applications. J Nano-and Electron Phys 15(3)

40.

Jawale MA, Pawar AB, Korde SK, Rakshe DS, William P, Deshpande N (2023) Energy management in electric vehicles using improved swarm optimized deep reinforcement learning algorithm. J Nano-and Electron Phys 15(3)

41.

Rashmi M, William P, Yogeesh N, Girija DK (2023) Blockchain-based cloud storage using secure and decentralised solution. In: Chaki N, Roy ND, Debnath P, Saeed K (eds) Proceedings of international conference on data analytics and insights, ICDAI 2023. ICDAI 2023. Lecture notes in networks and systems, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-99-3878-0_23

42.

Girija DK, Rashmi M, William P, Yogeesh N (2023) Framework for integrating the synergies of blockchain with AI and IoT for secure distributed systems. In: Chaki N, Roy ND, Debnath P, Saeed K (eds) Proceedings of international conference on data analytics and insights, ICDAI 2023. ICDAI 2023. Lecture notes in networks and systems, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-99-3878-0_22

Titel: Empirical Analysis of Machine Learning in Enhancing the E-Business Through Structural Equation Modeling
verfasst von: P. William
Md. Rageeb
Md. Usman Roja Boina
T. R. Vijaya Lakshmi
Ashish Sharma
Nikhil Kumar Marriwala
Verlag: Springer Nature Singapore
Buch: Mobile Radio Communications and 5G Networks
Print ISBN: 978-981-9706-99-0

Electronic ISBN: 978-981-9707-00-3

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-97-0700-3_45

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"