Aim
The goal of this course is to increase the understanding of methods for information retrieval, structuring and text mining, specially from Internet based sources.

Knowledge and understanding
For a passing grade the student must

• identify and formulate problems within web intelligence

• classify the problems in relation to his/her knowledge level

• understand and use methods from information retrieval

• analyze information sources to create structured information

• understand and use the basics of computational intelligence technology

Skills and abilities
For a passing grade the student must

• implement intelligent applications for knowledge extraction of medium complexity, using methodology from computational intelligence and information retrieval

Judgement and approach
For a passing grade the student must

• show skills to handle new methods and results

Contents
Information Retrieval: basic methods for ranking and searching, vector models, tf-idf relevance ranking. Information Retrieval systems.

Query Language: Different query languages for search in structured databases are presented.

Stuctured information: Indexing, searching and relevance ranking of search results. Exemplified with the aid of searches in structured databases (SRU/CQL).

Feature extraction: Extract properties and features for text documents.

Computational Intelligence: Basic methods for Computational Intelligence classification and knowledge extraction (as Neural Networks, Support Vector Machines, etc) are presented and experimented with. Using extracted features to implement topic classification of text documents.

Performance: Performance indicators like precision and recall.

Literature
Ricardo Baeza-Yates, Berthier Ribeiro-Neto: "Modern Information Retrieval", Addison-Wesley 1999, ISBN: 0-201-39829-X.
Articles and documents from the Web.
Course notes and labs