Construction mining

2021 ◽  
Vol 34 ◽  
Author(s):  
Fabian Barteld ◽  
Alexander Ziem
Keyword(s):  
Data Mining ◽  
Research Focus ◽  
Computational Implementation ◽  
Semantic Frames ◽  
Contemporary Standard

Abstract The German Constructicon Project (www.german-constructicon.de) aims at documenting grammatical constructions in contemporary standard German on the basis of annotated corpus examples, including relations between constructions and between constructions and evoked semantic frames. So far, the research focus has been mainly on the development and computational implementation of a constructicographic workflow (including a parsing pipeline) that allows for addressing any kind of constructions on varying levels of schematicity, idiomaticity, and abstractness. However, such an exemplar-driven procedure precludes us from systematically identifying constructional candidates. In this article, we scrutinize ways to operationalize and implement data-mining procedures to inductively identify construction candidates.

scholarly journals Analysis of Mining Social Media – A Learners Perspective

2020 ◽  
pp. 91-96
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Performance Metrics ◽  
Research Focus ◽  
Social Media Data ◽  
Data Mining Techniques ◽  
Huge Data ◽  
The Social ◽  
The Common ◽  
Media Data

In the world of digitalization the data play a key role. The data may be in structured or unstructured. The structured data uses data mining techniques to find the unknown pattern from the known data. But, the social media has huge data due to its rapid growth, the data were dynamic and unstructured. Due to this traditional data mining techniques will not be appropriate. The combinational approach of data mining and social media will provide the user to gain an insight and prominent idea how can be mined. Social media provides each individual to connect with the others depending on their interest. Every individual are accessing Face book, Twitter, LinkedIn, cademicia.edu, Google+ for sharing their views and thoughts, day-to-day happenings with any one or more of the above sites. This paper give an idea of the how those sites are classified based on their size, data, research focus, design issues and the types of the sites, types of users and the common approaches on social networks which will help the researchers how the social media, social networking websites structurally classified, studies the existing data mining techniques along with the performance metrics used in past researches and tools for retrieving social media data.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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