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A numerical design framework for unloading excavations in deep potash mining. [PDF]
Sci RepZhang Y +5 more
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Characteristics of overburden failure and evolution of fractures in fully mechanized top coal mining face. [PDF]
Sci RepWang X, Liu F.
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Sentiment Analysis and Opinion Mining
Synthesis Lectures on Human Language Technologies, 2012Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language.
Lei Zhang, B. Liu
semanticscholar +1 more source
2023
Abstract When patients cannot speak for themselves, clinicians look to surrogates to represent their wishes. Surrogate decision makers may not know the patient’s wishes; in which case, they typically try to think of the patient’s best interests or sometimes their own.
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Abstract When patients cannot speak for themselves, clinicians look to surrogates to represent their wishes. Surrogate decision makers may not know the patient’s wishes; in which case, they typically try to think of the patient’s best interests or sometimes their own.
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Fake News Detection on Social Media: A Data Mining Perspective
SKDD, 2017Social media for news consumption is a double-edged sword. On the one hand, its low cost, easy access, and rapid dissemination of information lead people to seek out and consume news from social media.
Kai Shu +4 more
semanticscholar +1 more source
1997
As databases grow in size and complexity the task of adding value to the wealth of data becomes difficult. Data mining has emerged as the technology to add value to enormous databases by finding new and important snippets (or nuggets) of knowledge. With large training sets, however, extremely large collections of nuggets are being extracted, leading to
Graham J. Williams, Zhexue Huang
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As databases grow in size and complexity the task of adding value to the wealth of data becomes difficult. Data mining has emerged as the technology to add value to enormous databases by finding new and important snippets (or nuggets) of knowledge. With large training sets, however, extremely large collections of nuggets are being extracted, leading to
Graham J. Williams, Zhexue Huang
openaire +1 more source
Data Mining for the Social Sciences, 2019
Data mining is the process of discovering interesting knowledge, such as patterns, associations, changes, anomalies and signiicant structures, from large amounts of data stored in databases, data warehouses, or other information repositories.
Kimberly Kirkpatrick
semanticscholar +1 more source
Data mining is the process of discovering interesting knowledge, such as patterns, associations, changes, anomalies and signiicant structures, from large amounts of data stored in databases, data warehouses, or other information repositories.
Kimberly Kirkpatrick
semanticscholar +1 more source
2005
Mining of association rules is one of the most adopted techniques for data mining in the most widespread application domains. A great deal of work has been carried out in the last years on the development of efficient algorithms for association rules extraction. Indeed, this problem is a computationally difficult task, known as NP-hard (Calders, 2004),
PSAILA, Giuseppe, MEO, ROSA
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Mining of association rules is one of the most adopted techniques for data mining in the most widespread application domains. A great deal of work has been carried out in the last years on the development of efficient algorithms for association rules extraction. Indeed, this problem is a computationally difficult task, known as NP-hard (Calders, 2004),
PSAILA, Giuseppe, MEO, ROSA
openaire +2 more sources