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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19456
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | Personalized Context-Aware Smartphone Usage Forecasting: A Machine Learning Model |
| Authors Name: | Dr.M.Deepa , S.Nathiya , R.Ramya |
| Download E-Certificate: | Download |
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IJRTI_188107
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| Published Paper Id: | IJRTI2309061 |
| Published In: | Volume 8 Issue 9, September-2023 |
| DOI: | |
| Abstract: | — In the past few decades, the field of human activity recognition has experienced significant growth. Numerous techniques for gathering data and evaluating it to find activity have been thoroughly researched. Contextual information pertinent to users' varied phone usage activities is captured through the device logs as a result of the growing popularity of recent enhanced features and context awareness in smart mobile phones. Context-aware customized systems may be created by simulating and forecasting how people will use their smartphones in different situations, such as temporal, geographical, or social information. In order to perform a context-aware analysis, we begin by applying five well-known machine learning methods for classifying data. We then present empirical assessments of an artificial neural network-based classification model, which is frequently used in deep learning, and perform a comparative analysis. A number of experiments are run on real mobile phone datasets gathered from users individually in order to evaluate the efficacy of these classifier-based context-aware models. Intuitive context-aware systems for smartphone users may be designed and built with the aid of the overall experimental findings and debates, which can be helpful to both researchers and application developers. |
| Keywords: | User behavior modeling, machine learning, Predictive analytics, and smartphone analytics |
| Cite Article: | "Personalized Context-Aware Smartphone Usage Forecasting: A Machine Learning Model ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 9, page no.462 - 466, September-2023, Available :http://www.ijrti.org/papers/IJRTI2309061.pdf |
| Downloads: | 000205052 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2309061
Registration ID:188107
Published In: Volume 8 Issue 9, September-2023
DOI (Digital Object Identifier):
Page No: 462 - 466 Country: NAMAKKAL, TAMIL NADU, INDIA Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2309061 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2309061 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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