Cluster Analysis as a First Step in the Knowledge Discovery Process

2000 ◽  
Vol 4 (4) ◽  
pp. 258-262 ◽  
Author(s):  
Andreas Rauber ◽  
◽  
Jan Paralic ◽  
Keyword(s):  
Cluster Analysis ◽  
Knowledge Discovery ◽  
Unsupervised Classification ◽  
Lessons Learned ◽  
Self Organizing Map ◽  
Discovery Process ◽  
Ticket Sales ◽  
Starting Point ◽  
Unsupervised Neural Network ◽  
Insight Into

Cluster analysis is one of the most prominent methods for the analysis of large, unknown datasets. It provides a particularly suitable tool for obtaining a first overview of data, forming a prominent starting point for further evaluation. . In this paper, we present some lessons learned during the application of two clustering approaches to the analysis of castle admission ticket sales data. A Bayesian unsupervised classification based on AutoClass and an unsupervised neural network, the Self-Organizing Map, are used to obtain a first impression of the available data to form the basis for further exploration. We show that this type of cluster analysis provides a suitable first step in the knowledge discovery process. The different types of result representation and their suitability of providing a first insight into datasets are analyzed and compared.

scholarly journals Profiling visitors of a national park in Italy through unsupervised classification of mixed data

2021 ◽  
pp. 135-140
Author(s):  
Giulia Caruso ◽  
Adelia Evangelista ◽  
Stefano Antonio Gattone
Keyword(s):  
Cluster Analysis ◽  
National Park ◽  
Unsupervised Classification ◽  
Mixed Data ◽  
Categorical Variables ◽  
Satisfaction Rate ◽  
Starting Point ◽  
Marketing Analysis ◽  
Over Time

Cluster analysis has for long been an effective tool for analysing data. Thus, several disciplines, such as marketing, psychology and computer sciences, just to mention a few, did take advantage from its contribution over time. Traditionally, this kind of algorithm concentrates only on numerical or categorical data at a time. In this work, instead, we analyse a dataset composed of mixed data, namely both numerical than categorical ones. More precisely, we focus on profiling visitors of the National Park of Majella in the Abruzzo region of Italy, which observations are characterized by variables such as gender, age, profession, expectations and satisfaction rate on park services. Applying a standard clustering procedure would be wholly inappropriate in this case. Therefore, we hereby propose an unsupervised classification of mixed data, a specific procedure capable of processing both numerical than categorical variables simultaneously, releasing truly precious information. In conclusion, our application therefore emphasizes how cluster analysis for mixed data can lead to discover particularly informative patterns, allowing to lay the groundwork for an accurate customers profiling, starting point for a detailed marketing analysis.

The Word Class Adjective in English Business Magazines Online

2018 ◽  
Vol 6 (2) ◽  
pp. 99-115
Author(s):  
Borislav Marušić ◽  
Sanda Katavić-Čaušić
Keyword(s):  
Empirical Study ◽  
Empirical Analysis ◽  
Word Formation ◽  
Word Class ◽  
Business English ◽  
Starting Point ◽  
Comprehensive Picture ◽  
English Syntax ◽  
The Empirical Analysis ◽  
Insight Into

Abstract The aim of this paper is to research the word class adjective in one sequence of the ESP: Business English, more precisely English business magazines online. It is an empirical study on the corpus taken from a variety of business magazines online. The empirical analysis allows a comprehensive insight into the word class adjective in this variety of Business English and makes its contribution to English syntax, semantics and word formation. The syntactic part analyses the adjective position in the sentence. The semantic part of the study identifies the most common adjectives that appear in English business magazines online. Most of the analysis is devoted to the word formation of the adjectives found in the corpus. The corpus is analysed in such a way that it enables its division into compounds, derivatives and conversions. The results obtained in this way will give a comprehensive picture of the word class adjective in this type of Business English and can act as a starting point for further research of the word class adjective.

Radical Subject Acceleration for Gifted Students: One School's Response

2019 ◽  
pp. 29-46
Author(s):  
Kaye Chalwell ◽  
Therese Cumming
Keyword(s):  
Gifted And Talented ◽  
Gifted Students ◽  
Subject Area ◽  
Lessons Learned ◽  
Gifted Student ◽  
Learning Needs ◽  
Mathematically Gifted ◽  
Support Students ◽  
Insight Into

Radical subject acceleration, or moving students through a subject area faster than is typical, including skipping grades, is a widely accepted approach to support students who are gifted and talented. This is done in order to match the student’s cognitive level and learning needs. This case study explored radical subject acceleration for gifted students by focusing on one school’s response to the learning needs of a ten year old mathematically gifted student. It provides insight into the challenges, accommodations and approach to radical subject acceleration in an Australian school. It explored the processes and decisions made to ensure that a gifted student’s learning needs were met and identified salient issues for radical subject acceleration. Lessons learned from this case study may be helpful for schools considering radical acceleration.

scholarly journals Particularities of data mining in medicine: lessons learned from patient medical time series data analysis

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Shadi Aljawarneh ◽  
Aurea Anguera ◽  
John William Atwood ◽  
Juan A. Lara ◽  
David Lizcano
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Knowledge Discovery ◽  
Time Series Data ◽  
Medical Patient ◽  
Lessons Learned ◽  
Physiological Signals ◽  
Knowledge Discovery In Databases ◽  
Series Data ◽  
Data Mining Techniques

AbstractNowadays, large amounts of data are generated in the medical domain. Various physiological signals generated from different organs can be recorded to extract interesting information about patients’ health. The analysis of physiological signals is a hard task that requires the use of specific approaches such as the Knowledge Discovery in Databases process. The application of such process in the domain of medicine has a series of implications and difficulties, especially regarding the application of data mining techniques to data, mainly time series, gathered from medical examinations of patients. The goal of this paper is to describe the lessons learned and the experience gathered by the authors applying data mining techniques to real medical patient data including time series. In this research, we carried out an exhaustive case study working on data from two medical fields: stabilometry (15 professional basketball players, 18 elite ice skaters) and electroencephalography (100 healthy patients, 100 epileptic patients). We applied a previously proposed knowledge discovery framework for classification purpose obtaining good results in terms of classification accuracy (greater than 99% in both fields). The good results obtained in our research are the groundwork for the lessons learned and recommendations made in this position paper that intends to be a guide for experts who have to face similar medical data mining projects.

scholarly journals Detection of drought events in Greece using daily precipitation

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Daily Precipitation ◽  
Hierarchical Cluster ◽  
Seasonal Distribution ◽  
Drought Severity ◽  
Severe Drought ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Insight Into

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.

scholarly journals Insight into capacity planning for cardiac catheterization services: Policy lessons learned from “Looking in the Mirror” over a decade

Health Policy ◽  
2009 ◽  
Vol 91 (3) ◽  
pp. 314-320 ◽  
Author(s):  
Mat Mercuri ◽  
Madhu K. Natarajan ◽  
Douglas H. Holder ◽  
Changchun Xie ◽  
Amiram Gafni
Keyword(s):  
Cardiac Catheterization ◽  
Capacity Planning ◽  
Lessons Learned ◽  
Insight Into

Designing the Person: Sociological Assumptions Embodied within the Architecture of Charles Rennie Mackintosh and Le Corbusier

2005 ◽  
Vol 14 (1) ◽  
pp. 141-162
Author(s):  
Clare Spencer
Keyword(s):  
Social Interaction ◽  
Comparative Study ◽  
Le Corbusier ◽  
Western Society ◽  
Architectural Practice ◽  
Individual Person ◽  
Interesting Insight ◽  
Starting Point ◽  
The Individual ◽  
Insight Into

This essay presents a comparative study of the sociological assumptions implicit, and to some extent explicit, in the work of two famous architects, Charles Rennie Mackintosh and Le Corbusier. The inhabitant implied through the architectural practice of Le Corbusier resembles Elias's homo clausus (closed person), the mode of self experience viewed by Elias as the dominant one in Western society and one which sees the individual person as a ‘thinking subject’ and the starting point of knowledge. Mackintosh's designs, in contrast, imply individual people closer to Elias‘s homines aperti, social beings who are shaped through social interaction and interdependence. This paper demonstrates how, as well as fulfilling social, cultural and political needs, architecture carries, within in its designs, certain assumptions about how people and how they do, and should, live. The adoption of an Eliasian perspective provides an interesting insight into how these assumptions can shape self-experience and social interaction in the buildings of each architect.

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