English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Since about 10 years ago, University of Applied Science and Technology (UAST)in Iran has admitted students in discontinuous associate degree by modularmethod, so that almost 100,000 students are accepted every year. Although thefirst aim of holding such courses was to improve scientific and skill level ofemployees, over time a considerable group of unemployed people have beeninterested to participate in these courses. According to this fact, in thispaper, we mine and analyze a sample data of accepted candidates in modular 2008and 2009 courses by using unsupervised and supervised learning paradigms. Inthe first step, by using unsupervised paradigm, we grouped (clustered) set ofmodular accepted candidates based on their student status and labeled data setsby three classes so that each class somehow shows educational and studentstatus of modular accepted candidates. In the second step, by using supervisedand unsupervised algorithms, we generated predicting models in 2008 data sets.Then, by making a comparison between performances of generated models, weselected predicting model of association rules through which some rules wereextracted. Finally, this model is executed for Test set which includes acceptedcandidates of next course then by evaluation of results, the percentage ofcorrectness and confidentiality of obtained results can be viewed.

Case study: Data Mining of Associate Degree Accepted Candidates by Modular Method