Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Identification of Consumer Buying Patterns using KNN in E-Commerce Applications Subject The topic of the resource buying behavior; Consumer behavior analysis; E- Commerce applications; K-Nearest Neighbor; Machine Learning Description An account of the resource In recent days, with the advancement of technologies, people use electronic medium to carry out their businesses. E-commerce is a process of allowing people to buy and sell products online using electronic medium. E-commerce has a wide range of customer base as well. The data generated through transaction helps the enterprises to develop the marketing strategy. The growth of this e-commerce application depends on several factors. Some of the factors are follows 1) Customer demand, 2) Analyzing buying pattern of the users, 3) Customer retention, 4) dynamic pricing etc. It is very difficult to analyze the buying pattern of customers as there is a wide range of customer base in the online platform. To overcome this problem, this research study discusses about the challenges and issues in e-commerce applications, also identifies and analyses the buying patterns of customer using various machine learning techniques. From the implementation it is identified that, KNN algorithm performed well while comparing it with various other machine learning algorithms. Performances of these algorithms have been analyzed using various matrices. For analyzing, the model is tested using e-commerce dataset (Amazon dataset downloaded from Kaggle.com). From the analysis it found that KNN algorithm computes and predicts better compared to other machine learning algorithms either Nae Bayes, or Random Forest, or Logistic Regression etc. 2023 IEEE. Creator An entity primarily responsible for making the resource Yasin W.; Harimoorthy K.; Vetriveeran D. Source A related resource from which the described resource is derived Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, pp. 187-192. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICPCSN58827.2023.00036" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICPCSN58827.2023.00036</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175243980&amp;doi=10.1109%2FICPCSN58827.2023.00036&amp;partnerID=40&amp;md5=5134f26d18311a790802b118153bd3a3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175243980&amp;doi=10.1109%2fICPCSN58827.2023.00036&amp;partnerID=40&amp;md5=5134f26d18311a790802b118153bd3a3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835032284-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Yasin W., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Harimoorthy K., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Vetriveeran D., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India