BIG DATA AND DATA MINING
cod. 1009070

Academic year 2020/21
1° year of course - Second semester
Professor
Flavio BERTINI
Academic discipline
Informatica (INF/01)
Field
Discipline informatiche
Type of training activity
Characterising
48 hours
of face-to-face activities
6 credits
hub:
course unit
in ITALIAN

Learning objectives

At the end of the course the student should have acquired knowledge and skills related to knowledge representation techniques and data mining algorithms. In particular, the student is expected to be able to:
- Know the main problems of Big Data and the objectives of Data Mining.
- Know the main techniques of knowledge representation.
- Knowing how to use formalisms appropriately for the representation of knowledge.
- Knowing how to use the main data mining techniques and algorithms.
- Knowing how to present a work project.
- Be able to analyze a problem and develop a data mining project.

Prerequisites

Good knowledge of the relational data model is strongly recommended. Knowledge of imperative programming languages.

Course unit content

■ Semi-structured and unstructured data models
■ The limits of SQL and an introduction to SQL/XML and XQuery
■ The information retrieval models and web information retrieval
■ The datawarehousing and data mining

Full programme

■ Part I
■ Introduction
■ Semi-structured and unstructured data models
■ Part II
■ XML introduction
■ SQL/XML language
■ XQuery language
■ XQuery and database management system
■ NoSQL database
■ Part III
■ Information Retrieval introduction
■ Ranking
■ Web Information Retrieval
■ Information Retrieval evaluation
■ Advanced methods
■ Part IV
■ Data analytics
■ Data warehouse
■ Data mining: association rule, classification and clustering

Bibliography

■ A. Moller, M. Schwartzbach - Introduzione a XML - Pearson, 2007, ISBN: 9788871923734
■ P.-N. Tan, M. Steinbach, V. Kumar - Introduction to data mining - Addison Wesley, 2005, ISBN: 0321420527
■ C.D. Manning, P. Raghavan, H. Schütze - Introduction to Information Retrieval - Cambridge University Press, 2008, ISBN: 0521865719
■ M. Golfarelli, S. Rizzi - Datawarehouse. Teoria e pratica della progettazione - McGraw-Hill Education, 2006, ISBN: 9788838662911

Teaching methods

Teaching activity partly in the classroom

Assessment methods and criteria

The assessment takes place with the discussion of an article. The student explores an advanced topic starting from a research paper among those proposed. The content of the paper and the related topic must be discussed during the exam through presentation slides prepared by the student.

Other information

- - -

2030 agenda goals for sustainable development

- - -

Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.scienze@unipr.it
T. 0521 90 5116

Quality assurance office

Education manager
dr. Claudia Buga
T. 0521 90 2842
Office e-mail: smfi.didattica@unipr.it
Manager e-mail: claudia.buga@unipr.it

President of the degree course

Prof. Alessandro Dal Palù
E. alessandro.dalpalu@unipr.it

Faculty advisor

Prof. Vincenzo Arceri
E. vincenzo.arceri@unipr.it

Career guidance delegate

Prof. Roberto Alfieri
E. roberto.alfieri@unipr.it

Tutor Professors

Prof. Enea Zaffanella
E. enea.zaffanella@unipr.it

Prof. Alessandro Dal Palù
E. alessandro.dalpalu@unipr.it

Erasmus delegates

Prof. Roberto Bagnara
E. roberto.bagnara@unipr.it
Student tutor dr. Anna Macaluso
E. anna.macaluso@studenti.unipr.it

Quality assurance manager

Prof. Enea Zaffanella
E. enea.zaffanella@unipr.it

Internships

Prof. Roberto Alfieri
E. roberto.alfieri@unipr.it

Student representatives: 
Greta Dolcetti 
Massimo Frati
Davide Tarpini