Quine-McCluskey: A Novel Concept for Mining the Frequency Patterns from Web Data

Bhandari, Bina; Goudar, R. H.; Kumar, K.C. Ravi

doi:10.5815/ijeme.2018.01.05

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…e statistical tool used for the analysis has been R, with the use of the QCA package that applies the advanced Quine-McCluskey algorithm [230]. Although the origins of the QCA method is not a new one [231,232], only recently the research has shown an increasing interest in its use [233][234][235][236] especially for the evaluation of particular qualitative elements in a company or to understand better the necessary conditions to achieve specific business objectives [231,[237][238][239][240][241][242][243][244][245].…”

Section: Methodsmentioning

confidence: 99%

An Analysis of the Long‐Term Sustainability of the Large Companies Included in the Original Standard and Poor’s 500 Index

Moya

Torres

Uche-Soria

2022

Discrete Dynamics in Nature and Society

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The changes generated by the natural economic and social development have configured a scenario where the companies’ survival is gradually decreasing. This process is also impacting on the big corporations that were strongly consolidated for many years. This research has analysed that which of these major companies of the Fortune 500 Index have adapted themselves over the years and have survived. After locating the surviving companies, this paper studied the presence of elements of business quality in each of these firms. Then, using a fuzzy set methodology, this study obtained results that identified some of the main elements that might be considered as inductors of the business durability in the case of the big corporations: the effectiveness of the companies, the coherence with the mission, and the capacity of organisation are essential for the long-term sustainability of the companies especially if they are associated with a formalised structure of governance. The results also conclude that the simple presence of these elements is not enough for the permanence of the companies and only the progresses and improvements in these variables can guarantee the sustainability of the companies.

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Section: Methodsmentioning

confidence: 99%

An Analysis of the Long‐Term Sustainability of the Large Companies Included in the Original Standard and Poor’s 500 Index

Moya

Torres

Uche-Soria

2022

Discrete Dynamics in Nature and Society

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“…In terms of resource search, both text resources and multimedia resources are necessary for online music courses. At the same time, semi-structured documents also provide additional information data such as hyperlinks and HTML [17]. The data mining classification structure of the whole web is shown in Figure 1.…”

Section: Web Based Layered Recommendation Algorithm and Its Applicati...mentioning

confidence: 99%

Web Based Online Hybrid Teaching Method of Network Music Course

Zitar²

2022

Int. J. Emerg. Technol. Learn.

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Today, with the rapid development of online course teaching, the demand for online courses is increasing day by day, and the demand for online mixed teaching of online music courses is also increasing rapidly. In the context of big data, the lengthy personalized screening process of users has become one of the problems to be solved. Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. The experimental results show that the average accuracy of the improved algorithm is 79.63% in the limited training times, and has better adaptability. It can be applied to the online hybrid teaching recommendation and screening of online music courses in dynamic changes.

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“…These can be simple sensors, but also wearables, smartphones, as well as all other smart devices of the Internet of Things environment [1]. Other examples of data stream sources may entail tools for the continuous measurement and monitoring of network traffic [2], web surfing logs [3], networked manufacturing machines in Industry 4.0 [4,5], virtual learning environments [6], online social networks [7], etc.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Hoeffding Decision Tree for Data Stream Classification

Ducange¹,

Marcelloni²,

Pecori³

2021

IJCIS

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Data stream mining has recently grown in popularity, thanks to an increasing number of applications which need continuous and fast analysis of streaming data. Such data are generally produced in application domains that require immediate reactions with strict temporal constraints. These particular characteristics make problematic the use of classical machine learning algorithms for mining knowledge from these fast data streams and call for appropriate techniques. In this paper, based on the well-known Hoeffding Decision Tree (HDT) for streaming data classification, we introduce FHDT, a fuzzy HDT that extends HDT with fuzziness, thus making HDT more robust to noisy and vague data. We tested FHDT on three synthetic datasets, usually adopted for analyzing concept drifts in data stream classification, and two real-world datasets, already exploited in some recent researches on fuzzy systems for streaming data. We show that FHDT outperforms HDT, especially in presence of concept drift. Furthermore, FHDT is characterized by a high level of interpretability, thanks to the linguistic rules that can be extracted from it.

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Quine-McCluskey: A Novel Concept for Mining the Frequency Patterns from Web Data

Cited by 7 publications

References 19 publications

An Analysis of the Long‐Term Sustainability of the Large Companies Included in the Original Standard and Poor’s 500 Index

An Analysis of the Long‐Term Sustainability of the Large Companies Included in the Original Standard and Poor’s 500 Index

Web Based Online Hybrid Teaching Method of Network Music Course

Fuzzy Hoeffding Decision Tree for Data Stream Classification

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