IOT data Fusion framework for e-commerce
The incapacity of the present marketing data management system to evaluate and process the association between marketing data provides uncertainty regarding the qualities of the products for marketing data mining and prevents effective data management. The article advances improved trends through th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917422001416 |
| _version_ | 1811339931473149952 |
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| author | Preeti Mahesh Kulkarni Bhaskar Nautiyal Sanjay Kumar Rani Medidha RajeshKumar Rameshbhai Savaliya Mundhe Eknath |
| author_facet | Preeti Mahesh Kulkarni Bhaskar Nautiyal Sanjay Kumar Rani Medidha RajeshKumar Rameshbhai Savaliya Mundhe Eknath |
| author_sort | Preeti Mahesh Kulkarni |
| collection | DOAJ |
| description | The incapacity of the present marketing data management system to evaluate and process the association between marketing data provides uncertainty regarding the qualities of the products for marketing data mining and prevents effective data management. The article advances improved trends through the exploration of forecastbusiness information from the e-commerce system.Enhance to context functionality of the e-commerce system by gathering relevant data from diverse sources.Appropriate extraction of marketing data from an e-commerce platform is achieved using distributed similarity and the information fusion approach to optimize association rules.Innovative results demonstrated the strong resilience and ability of the recommended approach to accomplish targeted marketing data mining. |
| first_indexed | 2024-04-13T18:34:45Z |
| format | Article |
| id | doaj.art-f73f679271aa4e79bb401b7c546c7984 |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-04-13T18:34:45Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-f73f679271aa4e79bb401b7c546c79842022-12-22T02:34:57ZengElsevierMeasurement: Sensors2665-91742022-12-0124100507IOT data Fusion framework for e-commercePreeti Mahesh Kulkarni0Bhaskar Nautiyal1Sanjay Kumar2Rani Medidha3RajeshKumar Rameshbhai Savaliya4Mundhe Eknath5Dr.Moonje Institute of Management & Computer Studies, Nashik, MS, India; Corresponding author.Graphic Era Deemed to be University, Visiting Faculty ,Graphic Era Hill University, Dehradun, Uttarakhand, IndiaDepartment of Computer Application, L.N Mishra Institute of Economic Development and Social Change, 1 Jawaharlal Nehru Marg, Patna, 800001, Bihar, IndiaDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhra Pradesh, IndiaHead of BCA Department, Ambaba Commerce College, MIBM & DICA, SABARGAM, Surat, Gujarat, 394325, IndiaRayat Shikshan Sanstha's, S. M. Joshi College Hadapsar, Pune-28, IndiaThe incapacity of the present marketing data management system to evaluate and process the association between marketing data provides uncertainty regarding the qualities of the products for marketing data mining and prevents effective data management. The article advances improved trends through the exploration of forecastbusiness information from the e-commerce system.Enhance to context functionality of the e-commerce system by gathering relevant data from diverse sources.Appropriate extraction of marketing data from an e-commerce platform is achieved using distributed similarity and the information fusion approach to optimize association rules.Innovative results demonstrated the strong resilience and ability of the recommended approach to accomplish targeted marketing data mining.http://www.sciencedirect.com/science/article/pii/S2665917422001416Business logic layerE-commerceSupplyMarketingAnd recall rate |
| spellingShingle | Preeti Mahesh Kulkarni Bhaskar Nautiyal Sanjay Kumar Rani Medidha RajeshKumar Rameshbhai Savaliya Mundhe Eknath IOT data Fusion framework for e-commerce Measurement: Sensors Business logic layer E-commerce Supply Marketing And recall rate |
| title | IOT data Fusion framework for e-commerce |
| title_full | IOT data Fusion framework for e-commerce |
| title_fullStr | IOT data Fusion framework for e-commerce |
| title_full_unstemmed | IOT data Fusion framework for e-commerce |
| title_short | IOT data Fusion framework for e-commerce |
| title_sort | iot data fusion framework for e commerce |
| topic | Business logic layer E-commerce Supply Marketing And recall rate |
| url | http://www.sciencedirect.com/science/article/pii/S2665917422001416 |
| work_keys_str_mv | AT preetimaheshkulkarni iotdatafusionframeworkforecommerce AT bhaskarnautiyal iotdatafusionframeworkforecommerce AT sanjaykumar iotdatafusionframeworkforecommerce AT ranimedidha iotdatafusionframeworkforecommerce AT rajeshkumarrameshbhaisavaliya iotdatafusionframeworkforecommerce AT mundheeknath iotdatafusionframeworkforecommerce |