Coursebooks

Distributed information systems

CS-423

Lecturer(s) :

Aberer Karl

Language:

English

Summary

This course introduces the key concepts and algorithms from the areas of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems.

Content

 

Information Retrieval

1.Information Retrieval - Introduction  2.Text-Based Information Retrieval 3.Vector Space Retrieval 4.Probabilistic Information Retrieval 5.Query Expansion 6.Inverted Index 7.Distributed Retrieval 8.Latent Semantic Indexing 9.Word Embeddings 10. Link-Based Ranking

Data Mining

1.Data Mining ' Introduction 2. Association Rule Mining 3. Clustering 4. Classification 5. Mining Social Graphs 6. Classification Methodology 7. Document Classification 8. Recommender Systems

Knowledge Bases

1. Semi-structured data 2. Semantic Web 3. RDF Resource Description Framework 4. Semantic Web Resources 5. Information Extraction 6. Taxonomy Induction 7. Ontology Mapping

 

Learning Prerequisites

Recommended courses

Introduction to Database Systems

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra + programming exercises (Python)

Assessment methods

25% Continuous evaluations with bonus system during the semester
75% Final written exam (180 min) during exam session

In the programs

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German