A Novel Framework for Recommending Data Mining Algorithm in Dynamic IoT Environment

Hossain, Mohammad Anwar; Ferdousi, Rahatara; Hossain, SK Alamgir; Alhamid, Mohammed F.; Saddik, Abdulmotaleb El

doi:10.1109/access.2020.3019480

Cited by 15 publications

(4 citation statements)

References 22 publications

(52 reference statements)

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“…Hossain et al made use of DM technology, and they tried to fnd out the interrelation of various factors from the data and found some new laws that were produced with the dynamic changes of various factors to guide the school sports research and teaching training and then found sports talents [15]. Li et al also discussed and studied the knowledge discovery of Web DM and unstructured data [16].…”

Section: Dm Technologymentioning

confidence: 99%

Teaching Reform of Ancient Literature Based on Credible BP Neural Network Technology in New Media Environment

Dai

2022

Security and Communication Networks

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Recent years have seen a progressive integration of the new media environment into people’s lives, studies, and employment, which has had a profound impact on China’s social economy. It is unavoidable to conduct the educational reform of classical literature in the age of new media. Data mining (DM) is a method for analysing and learning from data in databases and data warehouses using artificial intelligence. They work better together to create a solid foundation for decision-making analysis of businesses or pertinent departments in many fields. The BP algorithm can cause the weight to converge to a specific number, but it cannot ensure that that value is the error plane’s overall minimum. In order to correct the flaw that the BP neural network is prone to falling into local minima, the improved credible BP neural network used in this paper adopts the momentum factor. The findings demonstrate that there is little variation between the predicted value and the actual value achieved by applying the BP algorithm in the experimental group with order of magnitude standardised operation, and that this algorithm’s error has been decreased by 7.38%. It demonstrates that by examining students’ test scores in a data warehouse with a neural network algorithm in DM, we may discover potential patterns among the data.

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Section: Dm Technologymentioning

confidence: 99%

Teaching Reform of Ancient Literature Based on Credible BP Neural Network Technology in New Media Environment

Dai

2022

Security and Communication Networks

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“…Therefore the chances for data attack is reduced in the cloud computing process. A recommendation work on data mining algorithms [15] was structured to find out the best suitable algorithm for analyzing the big data with respect to their applications. The work says that all the data mining algorithms wont suite for all the applications.…”

Section: Related Workmentioning

confidence: 99%

December 2020

2020

JAICN

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Water is one of the basic resource need for every human in the world. The improper management of water storage system can lead a human life to any extent. As a result of technology development, the proposed model is developed to manage the water storage systems like dam and lake through remotely placed sensor signals. The sensors which are placed in the storage places gives the strength and storage capacity of the dam and lakes. Similarly the sensors which are placed at the sender dam or lake are used to predict the incoming water level to the receiver lake. This improves the prediction rate of flood in the river paths and this prediction allows the incoming dam to send off some waters outside to allocate some space for incoming waters. The data which are generated by the connected dams are stored in a cloud space for analyzing the water flow management. The sensors connected in a lake or dam is connected with IoT platform to avoid wire connections. Hence this model avoids sudden floods during rainy conditions and it ensures the physical strength of the lake and dam by continuous monitoring process.

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“…Unfortunately, few NRSs have been widely adopted due to reasons such as limited ability to provide personalized recommendations, inadequate suitability of existing algorithms for evolving nutritional needs, low quality and reliability of the data, low involvement of nutrition experts and so on [18][19][20][21][22][23][24] . A few studies have reviewed RSs in the food domain, addressing the technical aspects and research challenges of RSs [25][26][27] .…”

Section: Introductionmentioning

confidence: 99%

Recommendation Systems in Nutrition Field: A Scoping Review (Preprint)

Zhao,

Xue,

Chen

et al. 2024

Preprint

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BACKGROUND Recommendation systems (RS) have been widely used in the field of nutrition to promote the nutritional self-management, but few NRSs have been widely adopted due to various reasons. Limited studies have reviewed the RSs in food, with some methodological flaws including limited databases searches, high heterogeneity among included studies and rapidly evolving nature of evidence. OBJECTIVE We conducted a scoping review to summarize currently available recommendation systems applied in nutrition (NRS) including published articles, patents and application software and explore the potential gaps between development and implementation. METHODS We conducted a comprehensive search of seven bibliographic databases, two patent databases, four mobile apps store and three websites engines for this scoping reviews. Data extraction was conducted by four reviewers, a pilot study was performed before formal extraction, and the interrater agreement percentage needed to be >75%. Discrepancies were resolved by consensus or the involvement of a third reviewer. Frequency count and narrative summaries were performed for each study. RESULTS A total of 877 NRSs were included and half of them were released after 2022 (n=423, 48.2%) and 155 (17.7%) were from China. The most users were overweight or obese population (n=152, 17.3%), the primary inputs being self-reported data on nutritional status, diet, and exercise (the same n=157, 17.9% for every one), the primary output being nutrition plans (n=254, 29.0%), and the main audience being general population (n=244, 27.8%). Of 49 studies published in journals or essays, a few researchers from the nutrition filed were reported (n=4, 3.6%), the primary data were from public survey (n=22, 46.8%). Forty studies reported the evaluation stage, with incomplete processes and the lack of nutritional outcome. Of the 18 artificial intelligence technologies used in the studies, four could automatically update systems by themselves, and two were technologies proposed in the last decade. In addition, three recommendation algorithms were identified, only one was the latest knowledge-based algorithm that can improve precise matching. CONCLUSIONS While NRSs has primarily focused on the general population, there is a growing demand for professional NRSs tailored to special populations that incorporate dynamic updates and enhanced individual identification. Standardized evaluation of NRSs based on their technical performance and clinical impact can effectively support their public application in future. CLINICALTRIAL The protocol was registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/VF7NB)

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A Novel Framework for Recommending Data Mining Algorithm in Dynamic IoT Environment

Cited by 15 publications

References 22 publications

Teaching Reform of Ancient Literature Based on Credible BP Neural Network Technology in New Media Environment

Teaching Reform of Ancient Literature Based on Credible BP Neural Network Technology in New Media Environment

December 2020

Recommendation Systems in Nutrition Field: A Scoping Review (Preprint)

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