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Bhandari, Inderpal; Colet, Edward; Parker, J.; Pines, Zachary; Pratap, Rajiv; Ramanujam, K. S.

doi:10.1023/a:1009782106822

Cited by 94 publications

(6 citation statements)

References 2 publications

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“…This following site explains the best way to maneuver the whole ranking up process for scouts [12]. While yes, it might explain the basics, it doesn't really do the job that well.…”

Section: Related Workmentioning

confidence: 99%

A User-Friendly Mobile Application to Accelerate the Attainment of the First Class Rank in the Boy Scouts of America using the Unity Engine

Jia,

Morris

2023

Advances in Computing &Amp; Information Technologies

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The process of Scouts within the Boy Scouts of America ranking up to First Class, and eventually Eagle, can be quite gruesome and challenging [1]. Though there are various resources online ranging from articles and videos that explain how to potentially speed up the ranking process, none of them actually give an effective solution to the problem. Scouts nowadays lack things like attention span because of the harmful side of social media, especially TikTok [2]. They don’t want tips and tricks on how to rank faster, and they also don’t want to flip through massive textbooks to find the answers to requirements. They just want straightforward and quick answers to their problems without any stalling. This is exactly what the Trail to First Class app is. It gives them quick answers to their problems without any ties. Though, the app is not perfect. There is a severe limitation that if some requirements require scouts to, for example, identify things around their geological area, the app cannot help them because providing the answers to every single possible geological area would be quite inefficient. Though something like this might be possible in the future, it definitely cannot come now. Despite the limitations, the app is more than enough to provide scouts with all the resources they need in order to accelerate their ranking process.

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“…This following site explains the best way to maneuver the whole ranking up process for scouts [12]. While yes, it might explain the basics, it doesn't really do the job that well.…”

Section: Related Workmentioning

confidence: 99%

A User-Friendly Mobile Application to Accelerate the Attainment of the First Class Rank in the Boy Scouts of America using the Unity Engine

Jia,

Morris

2023

Advances in Computing &Amp; Information Technologies

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“…There have been several published research studies applying machine learning and deep learning to predict results in a variety of sports. The application of data mining in basketball was started in the 1990s by IBM named Advanced Scout (Colet & Parker, 1997). The purpose of this tool was to assist the NBA management team to discover the hidden patterns from basketball statistics using data mining techniques.…”

Section: Literature Reviewmentioning

confidence: 99%

The application of machine learning and deep learning in sport: predicting NBA players’ performance and popularity

Nguyen

et al. 2021

Journal of Information and Telecommunication

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“…There are DM applications even in sports. Bhandari (1997) describe one application used by National Basketball Association (NBA) coaching staffs to discover interesting patterns in basketball game data.…”

Section: Data Mining and Knowledge Discovery In Databasesmentioning

confidence: 99%

Extending QMBE Language with Clustering

Azevedo

Santos

2013

International Journal of Decision Support System Technology

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Business Intelligence (BI) is an important area of the Decision Support Systems (DSS) discipline. Over the past years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. This creates a gap between DM and BI systems. With the purpose of closing this gap a new DM language for BI, named as Query-Models-By-Example (QMBE), was envisaged and implemented with success, but addressing only classification rules. This paper presents an extension of QMBE language to include clustering. This represents one more step towards the integration of DM with BI, which constitutes an important issue.

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Untitled

Cited by 94 publications

References 2 publications

A User-Friendly Mobile Application to Accelerate the Attainment of the First Class Rank in the Boy Scouts of America using the Unity Engine

A User-Friendly Mobile Application to Accelerate the Attainment of the First Class Rank in the Boy Scouts of America using the Unity Engine

The application of machine learning and deep learning in sport: predicting NBA players’ performance and popularity

Extending QMBE Language with Clustering

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