Data Mining II

Code:

CC4024

Acronym:

CC4024

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2017/2018 - 2S

Active?	Yes
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master in Computer Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:CC	21	Study plan since 2014/2015	1	-	6	42	162
M:ENM	9	Official Study Plan since 2013-2014	1	-	6	42	162
MI:ERS	15	Plano Oficial desde ano letivo 2014	4	-	6	42	162
M:M	13	Plano de Estudos do M:Matemática	1	-	6	42	162

Teaching language

Inglês ou, caso possível, português

Objectives

Identification and application of data mining techniques to extract knowledge from different data sources (e.g. text, web).

Learning outcomes and competences

The student is able to:
- recognize different problems solvable through the use of data mining techniques discussed and detailed in content;
- identify and specify data mining tasks similar to those discussed;
- obtain and pre-process data for the algorithms and tasks addressed;
- understand and use data mining algorithms;
- obtain, interpret, evaluate and use data mining models;
- Implement some of the algorithms and propose changes to improve them.

Working method

Presencial

Program

- Association Pattern Mining: frequent itemsets and association rules; Apriori algorithm; itemsets summarization and rules selection; FP-Growth algorithm. 
- Sequential Pattern Mining: GSP algorithm; PrefixSpan algorithm.
- Web Mining: information retrieval; recommender systems; link analysis.
- Text Mining: document clustering; document classification.
- Outlier Mining: challenges; unsupervised, semi-supervised and supervised techniques.

Mandatory literature

Liu Bing 1963-; Web data mining. ISBN: 9783642194597 hbk
Hand David 1950-; Principles of data mining. ISBN: 9780262082907 hbk

Complementary Bibliography

Charu C. Aggarwal; Data Mining - The Texbook, Springer, 2015. ISBN: 978-3-319-14141-1

Teaching methods and learning activities

Theoretical-practical classes where the themes covered in the program will be exposed and some practical examples of application will be provided

 

Software

RStudio
R

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho prático ou de projeto	30,00
Total:	100,00

Eligibility for exams

In order to be eligible for exams, students must: participate either in the two theoretical tests provided in the curricular unit or in the final exam consisting of two parts concerning the contents of test 1 and test 2; have a minimum grade the practical assignment of 35% (7 out of 20).

Calculation formula of final grade

The assessment of the unit is distributed and it is composed of two (2) theoretical tests and one (1) practical assignment.

The final grade is given as a weighted average of the practical grade and the theoretical grades using the following formula:

GFinal = 0.70 * GT + 0.30 * GP

where,
GT is the average of the grades on the two theoretical tests or of the final exams and
GP is given by the grade of the practical assignment

There will be 2 tests during the semester. These are not compulsory, but everyone that obtains minimum grade in each test, and in each practical assignment, and whose final grade (GFinal) is positive (above 9.5), does not need to go to the final exam.

Minimum grade of the tests and the practical assignment: 35% (7 out of 20)

Examinations or Special Assignments

The theoretical tests will take place in two theoretical classes, one in the middle of the semester and the other at the end of it.

The practical assignment will be announced during the semester and should be completed by at the end of the semester on a date to be announced.

Classification improvement

The evaluation of the practical assignment is not subject to improvement. The student can improve the theoretical grade by the two final exams.

Observations

All the provided material (slides, recommended books, etc.) is in the English language.