Atomic Data Mining Numerical Methods, Source Code SQlite with Python

Khwaldeh, A.; Tahat, Amani; Martı́, Jordi; Tahat, Mofleh

doi:10.1016/j.sbspro.2013.02.046

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Many scholars in various fields have been committed to promoting data mining for a long time. Layton [48,49], Khwaldeh [50] and many other researchers introduced data mining based on Python in detail in their works, and these demystify data mining [51][52][53].…”

Section: Data Mining Technologymentioning

confidence: 99%

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

Xiong

Yan

Yao³

et al. 2022

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In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user’s attention factors, score the emotional tendency, and analyze the user’s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and quantify the emotional orientation matching. Based on the obtained data, we design a visual interaction logic and usability test. These prove that the proposed method is feasible and effective.

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Section: Data Mining Technologymentioning

confidence: 99%

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

Xiong

Yan

Yao³

et al. 2022

Information

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“…, etc., but this DBMS allows collaborative online data mining inside the system and using Python codes via the internet, which is conducive to finding atomic data mining from the literature and adding them to a user's profile. This DBMS has been fully described in a recently published data mining Python book [4] and conference papers. [5] The idea of this DBMS comes to solve several problems of atomic data resources and provides a work station with all facilities where the user need not be an expert in the physical theories and/or programming language.…”

Section: Introductionmentioning

confidence: 99%

AJAC: Atomic data calculation tool in Python

Tahat

Martı́

Tahat³

et al. 2013

Chinese Phys. B

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In this work, new features and extensions of a currently used online atomic database management system are reported. A multiplatform flexible computation package is added to the present system, to allow the calculation of various atomic radiative and collisional processes, based on simplifying the use of some existing atomic codes adopted from the literature. The interaction between users and data is facilitated by a rather extensive Python graphical user interface working online and could be installed in personal computers of different classes. In particular, this study gives an overview of the use of one model of the package models (i.e., electron impact collisional excitation model). The accuracy of computing capability of the electron impact collisional excitation in the adopted model, which follows the distorted wave approximation approach, is enhanced by implementing the Dirac R-matrix approximation approach. The validity and utility of this approach are presented through a comparison of the current computed results with earlier available theoretical and experimental results. Finally, the source code is made available under the general public license and being distributed freely in the hope that it will be useful to a wide community of laboratory and astrophysical plasma diagnostics.

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Deep learning based text classification with Web Scraping methods

Ertam

2018

2018 International Conference on Artificial Intelligence and Data Processing (IDAP)

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Atomic Data Mining Numerical Methods, Source Code SQlite with Python

Cited by 3 publications

References 2 publications

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

AJAC: Atomic data calculation tool in Python

Deep learning based text classification with Web Scraping methods

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