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LEVERAGING INNOVATIVE MARKETING STRATEGIES IN RETAIL THROUGH DISTRIBUTED DATA AND KNOWLEDGE -BASED SYSTEMS

Affiliation
PhD student, Tashkent State University of Economics

Abstract

In today’s competitive retail landscape, innovative marketing strategies are essential. This paper explores how distributed data systems and knowledge -based technologies can enhance marketing effectiveness. By analyzing data from diverse sources and applyi ng AI -driven insights, retailers can better understand customer behavior and market trends. Knowledge -based systems enable personalized marketing and precise targeting. A distributed approach improves scalability, responsiveness, and security. The paper al so addresses data privacy challenges. In conclusion, leveraging advanced analytics and intelligent systems helps retailers gain a competitive edge and achieve sustainable growth.

Keywords

innovative marketing strategies, retail industry, distributed data, knowledge -based systems, customer engagement, advanced analytics, competitive advantage


References

  1. Forestiero, A. (2021). Metaheuristic algorithm for anomaly detection in Internet of Things leveraging on a neural -driven multiagent system. Knowledge -Based Systems.
  2. Wang, H., Xu, Z., & Pedrycz, W. (2017). An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities. Knowledge - Based Systems.
  3. Caldarola, E. G., Modoni, G. E., & Sacco, M. (2018). Enhancing the Workforce Skills and Competences by Leveraging a Human -Centered Knowledge -Based System in the Rise of Industry 4.0. Intelligent Systems.
  4. Wu, Q., Wu, J., Shen, J., Du, B., & Telikani, A. (2022). Distributed agent -based deep reinforcement learning for large scale traffic signal control. Knowledge -Based Systems.
  5. Villegas, N. M., Sánchez, C., & Díaz -Cely, J. (2018). Characterizing context - aware recommender systems: A systematic literature review. Knowledge -Based Systems.
  6. De Santo, A., Galli, A., Moscato, V., & Sperlì, G. (2021). A deep learning approach for semi -supervised community detection in Online Social Networks. Knowledge -Based Systems.
  7. García -Sánchez, F., Paredes -Valverde, M. (2017). KBS4FIA: Leveraging advanced knowledge -based systems for financial information analysis. Lenguaje Natural.
  8. Chang, V. (2017). Towards data analysis for weather cloud computing. Knowledge -Based Systems.
  9. Catelli, R., Casola, V., De Pietro, G., Fujita, H. (2021). Combining contextualized word representation and sub -document level analysis through Bi - LSTM+ CRF architecture for clinical de -identification. Knowledge -Based Systems.
  10. Gupta, S., Justy, T., Kamboj, S., Kumar, A. (2021). Big data and firm marketing performance: Findings from knowledge -based view. Forecasting and Social.
  11. Ngai, E.W.T., Lee, M.C.M., Luo, M., Chan, P.S.L. (2021). An intelligent knowledge -based chatbot for customer service. Commerce Research and.
  12. Benítez -Hidalgo, A., Barba -González, C. (2021). TITAN: A knowledge - based platform for Big Data workflow management. Knowledge -Based Systems.
  13. Halawi, L., McCarthy, R., Aronson, J. (2017). Success stories in knowledge management systems. Information Systems.
  14. Kazanjian, R.K., Drazin, R. (2017). Implementing strategies for corporate entrepreneurship: A knowledge -based perspective. Creating a new mindset.
  15. Zhang, W., Jiang, Y., Zhang, W. (2019). Capabilities for collaborative innovation of technological alliance: A knowledge -based view. IEEE Transactions on.
  16. Varadarajan, R. (2020). Customer information resources advantage, marketing strategy and business performance: A market resources based view. Industrial Marketing Management.
  17. Mohammadi, V., Rahmani, A.M., Darwesh, A. (2021). Trust -based Friend Selection Algorithm for navigability in social Internet of Things. Knowledge -Based Systems.
  18. Zhao, G., Lou, P., Qian, X., Hou, X. (2020). Personalized location recommendation by fusing sentimental and spatial context. Knowledge -Based Systems.
  19. Wang, Y., Sun, X., Li, X., Zhang, W., Gao, X. (2021). Reasoning like humans: on dynamic attention prior in image captioning. Knowledge -Based Systems.
  20. Horng, J.S., Liu, C.H., Chou, S.F., Yu, T.Y., Hu, D.C. (2022). Role of big data capabilities in enhancing competitive advantage and performance in the hospitality sector: Knowledge -based dynamic capabilities view. Journal of Hospitality and.
  21. Daudert, T. (2021). Exploiting textual and relationship information for fine - grained financial sentiment analysis. Knowledge -Based Systems.
  22. Agaram, M.K. (2019). Intelligent foundations for knowledge -based systems. Science, Technology and Engineering Systems.
  23. Fernandez -Basso, C., Francisco -Agra, A. J. (2019). Finding tendencies in streaming data using big data frequent itemset mining. Knowledge -Based Systems.
  24. del Carmen Rodríguez -Hernández, M., Ilarri, S. (2021). AI -based mobile context -aware recommender systems from an information management perspective: Progress and directions. Knowledge -Based Systems.
  25. Khosravani, M. R., Nasiri, S., Reinicke, T. (2022). Intelligent knowledge - based system to improve injection molding process. Journal of Industrial Information.
  26. Villegas, N. M., Sánchez, C., Díaz -Cely, J. (2018). Characterizing context - aware recommender systems: A systematic literature review. Knowledge -Based Systems.
  27. Abu Amuna, Y. M., Al Shobaki, M. J., Abu -Naser, S. S. (2017). The role of knowledge -based computerized management information systems in the administrative decision -making process.
  28. Chowdhury, S., Budhwar, P., Dey, P. K., Joel -Edgar, S. (2022). AI -employee collaboration and business performance: Integrating knowledge -based view, socio - technical systems and organizational socialization framework. Journal of Business Research.
  29. Horng, J. S., Liu, C. H., Chou, S. F., Yu, T. Y., Hu, D. C. (2022). Role of big data capabilities in enhancing competitive advantage and performance in the hospitality sector: Knowledge -based dynamic capabilities view. Journal of Hospitality and Tourism Ma nagement.
  30. Bozorgi, A., Samet, S., Kwisthout, J., Wareham, T. (2017). Community -based influence maximization in social networks under a competitive linear threshold model. Knowledge -Based Systems.
  31. Badii, C., Bellini, P., Cenni, D., Difino, A., Nesi, P. (2017). Analysis and assessment of a knowledge -based smart city architecture providing service APIs. Future Generation Computer Systems.

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