Clothing Product Reviews Mining Based on Machine Learning

Hong, Qing; Feng, Peifei; Cheng, Zhi-Quan

doi:10.3991/ijoe.v11i9.5069

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Machine Learning [1] is an approach to enhance the performance of the machines. This is done by developing efficient algorithms, which makes the system to learn by experience for a given task.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Liver Disease using Regression Tree

Vinutha¹,

Chandrika²

2021

Int. J. Onl. Eng.

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Abstract— Data Mining plays a decisive role especially in medical domain. Decision trees are predominant model in machine learning. Decision trees are simple and very effective classification approach. The decision tree identifies the utmost prime features of a given problem. One of the most common disease in India is Liver Cirrhosis. It is distinctly difficult to uncover Liver Cirrhosis in its initial stage. However early diagnosis of Liver Cirrhosis is highly important.The liver disease data set has a collection of distinguishing features that affect the healthy state of a patient. Machine Learning methods enable knowledge acquisition in early stages and use of this acquired knowledge plays an important role in solving problems like suppose if we want to predict whether the patient with the Liver Cirrhosis has also been suffering from Hepatitis C or not. In order to easily arrive at this knowledge certainly there is a need for fully integrated system. In this paper the collected Liver disease data set is analyzed and prognosticated whether the patient is suffering from liver cirrhosis or not.

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Section: Introductionmentioning

confidence: 99%

Prediction of Liver Disease using Regression Tree

Vinutha¹,

Chandrika²

2021

Int. J. Onl. Eng.

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Text Mining for Supply Chain Risk Management in the Apparel Industry

2021

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Text mining tools are now widely used for the efficient management of information and resources in business, academic and research organizations. This paper provides a comprehensive overview of research articles on the application of text mining techniques in the field of Supply Chain Risk Management and the apparel industry. Research articles published between 2000 and 2020, were obtained from various journals through two online databases, i.e., SCOPUS and IEEE Xplore. Through a systematic approach following PRISMA guidelines, 370 research papers were screened, filtered and finally classified into three main areas: Supply Chain Risk Management and outsourcing in the apparel industry, application of text mining in Supply Chain Risk Management and application of text mining in the apparel industry. In this study, we have identified a comprehensive list of various available data sources for text mining, methodologies and risks associated with outsourcing in the apparel industry. We classify the gaps in expanding the application of text mining in the apparel industry’s Supply Chain Risk Management. Extracting useful information from online newspapers through text mining could vividly enhance the ability to monitor supply chain risks and provide the ability to link data to provide decision makers with the right information at the right time.

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Clothing Product Reviews Mining Based on Machine Learning

Cited by 2 publications

References 6 publications

Prediction of Liver Disease using Regression Tree

Prediction of Liver Disease using Regression Tree

Text Mining for Supply Chain Risk Management in the Apparel Industry

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