Information Retrieval and Data Mining
The following are last minute news you should be aware of ;-)
25/10/2015: Added slides on data representation and decision trees 11/10/2015: Added link to Teaching Assistant website to get his material 09/10/2015: First edition of IRDM website is out, stay tuned!
Contents
Course Aim & Organization
The course covers tools and systems adopted to handle big data, e.g., large collections of textual data. In the first part, the course focuses on the analysis of information embedded in large collections, using tools that range from decision trees, classification rules, association rules, graph-based link analysis. The second part of the course covers the efficient retrieval of information, discussing the algorithms and data structures adopted to enable answering keyword based queries, as well as indexing methods to enable fast search.
Teachers
The course is composed by a blending of lectures and exercises by the course teacher and a teaching assistant.
- Matteo Matteucci: the course teacher
- Luca Bondi: the teaching assistant
Course Program
The course outline is:
- Data mining
- The Data Mining process
- Decision Trees and Decision Rules
- Rule Induction Methods
- Association Rules
- Frequent Itemset Analysis
- Web information retrieval
- Web modelling and crawling
- Graph-based retrieval models (PageRank, HITS)
- Text-based information retrieval
- IR models (Boolean models, vector space models, probabilistic models)
- Evaluation of IR systems
- Text processing
- Advanced IR models (Latent Semantic Indexing)
- Indexing
- Inverted indexing
- Multidimensional indexing
- Rank aggregation
Detailed course schedule
A detailed schedule of the course can be found here; topics are just indicative while days and teachers are correct up to some last minute change (I will notify you by email). Please note that not all days we have lectures!!
Note: Lecture timetable interpretation * On Mondays, in V.08, starts at 15:30 (quarto d'ora accademico), ends at 18:15 * On Fridays, in V.08, starts at 08:30 (quarto d'ora accademico), ends at 10:15
| Date | Day | Time | Room | Teacher | Topic |
| 05/10/2015 | Monday | 15:15 - 18:15 | V08 | Matteo Matteucci | Course Introduction |
| 09/10/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | The Data Mining Process |
| 12/10/2015 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | Introduction to Information Retrieval |
| 16/10/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | Data representation and coding |
| 19/10/2015 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | Basic models for Information Retrieval |
| 23/10/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | Introduction to probability |
| 26/10/2015 | Monday | -- | -- | -- | No Lecture Today |
| 30/11/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | Entropy and information gain |
| 02/11/2015 | Monday | -- | -- | -- | No Lecture Today |
| 06/11/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | Decision Trees |
| 09/11/2015 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | |
| 13/11/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | |
| 16/11/2015 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | |
| 20/11/2015 | Friday | -- | -- | -- | No Lecture Today |
| 23/11/2015 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | |
| 27/11/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | |
| 30/11/2015 | Monday | -- | -- | -- | No Lecture Today |
| 04/12/2015 | Friday | 08:15 - 12:15 | V.S8-B | Matteo Matteucci | |
| 07/12/2015 | Monday | - | - | - | No Lecture Today |
| 11/12/2014 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | |
| 14/12/2014 | Monday | 15:15 - 18:15 | V.S8-B | Luca Bondi | |
| 18/12/2015 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | |
| 21/12/2014 | Monday | 15:15 - 17:15 | V.S8-B | Luca Bondi | |
| 08/01/2016 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci | |
| 11/01/2016 | Monday | 15:15 - 18:15 | V.S8-B | Matteo Matteucci | |
| 15/01/2016 | Friday | 08:15 - 10:15 | V.S8-B | Matteo Matteucci |
Course Evaluation
Course evaluation is through a written exam covering the whole program
Teaching Material
Teachers Slides
In the following you can find the lecture slides used by the teacher and the teaching assistants during classes.
Teacher Lectures:
- [2015] Course introduction: introductory slides of the course with useful information about the grading, and the course logistics.
- [2015] Data Mining: Data Mining introduction, historical perspective and related topics, the data mining process.
- [2015] Data Representation: Data representation types and issues, file formats and public datasets.
- [2015] Decision Trees: Recap on probability, condiational entropy and information gain, decision trees.
Teaching Assistand Lectures can be found directly on Luca Bondi website.
Additional Resources
Papers and links useful to integrate the textbook
* TBC
Past Exams and Sample Questions
Since 2015/2016 the course has changed teacher, this might have an impact on the exams format as well. Some examples from the past year can be found here, please expect differences:
Online Resources
The following are links to online sources which might be useful to complement the material above
* TBC
