Investigation of Mining Association Rules on XML Document

Association rules are used in different data mining applications, including Web mining, intrusion detection, and bioinformatics. This study mainly discusses the COVID‐19 patient diagnosis and treatment data mining algorithm based on association rules. General data The key time interval during the main diagnosis and treatment process (including onset to dyspnea, first diagnosis, admission, mechanical ventilation, death, and the time from first diagnosis to admission, etc.), the cause of death by laboratory examination, and so forth. The frequency of drug use was counted and association rule algorithm was used to analyse and study the effect of drug treatment. The results could provide reference for rational drug use in COVID‐19 patients. In this study, in order to improve the efficiency of data mining in data processing, it is necessary to pre‐process these data. Secondly, in the application of this data mining, the main objective is to extract association rules of COVID‐19 complications. So its properties for mining should be various diseases. Therefore, it is necessary to classify individual disease types. During the construction of association rules database, the data in the data warehouse is analysed online and the association rules data mining is analysed. The results are stored in the knowledge base for decision support. For example, the prediction results of the decision tree can be displayed at this level. After the construction of the mining model, the display interface can be mined, and the decision‐maker can input the corresponding attribute value and then predict it. 0.76% of people had both COVID‐19, CHD and hypertension, while 46.5% of people with COVID‐19 and CHD were likely to have hypertension. This study is helpful to analyse the imaging factors of COVID‐19 disease.

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“…For the data set x, the expected information is calculated as (Sumangali, 2016):

F ((),,,, n_{1}, n_{2}, \dots, n_{m}) = - \sum_{j = 1}^{m} P ((), B_{j}) \log_{2} ((), P ((), B_{j}))

…”

Section: Data Mining For Diagnosis and Treatment Of Patients With New...mentioning

confidence: 99%

COVID‐19 patient diagnosis and treatment data mining algorithm based on association rules

Shan

Miao

2021

Expert Systems

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“…The above-stated itemsets fulfilled the threshold value of minimum utility and placed entire itemsets in ascending order. The total number of itemsets is 19, and the k value must be specified to display maximum utility itemsets [12] [13]. When the value of k is 10, then it exhibits the top-10 HUIs with their utility item values.…”

Section: An Examplementioning

confidence: 99%

An Approach for Mining Top-k High Utility Item Sets (HUI)

Ramana¹,

Muralidhar²,

Balusa³

et al. 2023

IJRITCC

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Itemsets have been extracted by utilising high utility item (HUI) mining, which provides more benefits to the consumer. This could be one of the significant domains in data mining and be resourceful for several real-time implementations. Even though modern HUI mining algorithms may identify item sets that meet the minimum utility threshold, However, fixing the minimum threshold utility value has not been a simple task, and often it is intricate for the consumers when we keep the minimum utility value low. It might generate a massive amount of itemsets, and when the value is at its maximum, it might provide a smaller amount of itemsets. To avoid these issues, top-k HUI mining, where k represents the number of HUIs to be identified, has been proposed. Further, in this manuscript, the authors projected an algorithm called the top-k exact utility (TKEU) algorithm, which works without computing and comparing transaction weighted utilisation (TWU) values and deliberates the individual utility item values for deriving the top-k HUI. The datasets are pre-processed by the proposed algorithm to lessen the system memory space and to provide optimal outcomes for condensed datasets.

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Syntax Recovery for Uniface as a Domain Specific Language

Yafi

Fatima

2018

2018 UKSim-AMSS 20th International Conference on Computer Modelling and Simulation (UKSim)

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Investigation of Mining Association Rules on XML Document

Cited by 3 publications

References 13 publications

COVID‐19 patient diagnosis and treatment data mining algorithm based on association rules

COVID‐19 patient diagnosis and treatment data mining algorithm based on association rules

An Approach for Mining Top-k High Utility Item Sets (HUI)

Syntax Recovery for Uniface as a Domain Specific Language

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