Course syllabus

Webb-intelligens och informationssökning
Web Intelligence and Information Retrieval

EITN01, 7,5 credits, A (Second Cycle)

Valid for: 2012/13
Decided by: Education Board 1
Date of Decision: 2012-03-19

General Information

Elective for: C4, D4, D4-ks
Language of instruction: The course might be given in English

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.

Learning outcomes

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

Competences and skills
For a passing grade the student must

• be able to implement intelligent applications for knowledge extraction of medium complexity, using methodology from 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.

Basic methods for 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.

Examination details

Grading scale: TH
Assessment: Written examination, passed laboratories and assignments.

Parts
Code: 0113. Name: Laboratory Work.
Credits: 4. Grading scale: UG. Assessment: Approved laboratory work.
Code: 0213. Name: Assignments.
Credits: 0. Grading scale: UG. Assessment: Approved written assignments.
Code: 0313. Name: Written Examination.
Credits: 3,5. Grading scale: TH. Assessment: Approved written exam.

Admission

Admission requirements:

• EDA011 or EDA016 Programming, First Course

Required prior knowledge: FMA420 Linear Algebra.
The number of participants is limited to: No
The course might be cancelled: If the number of applicants is less than 8.
The course overlaps following course/s: EIT031

Reading list

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

Contact and other information

Course coordinator: Universitetslektor Anders Ardö, Anders.Ardo@eit.lth.se
Course homepage: http://www.eit.lth.se/course/eitn01
Further information: With less than 16 participants, the course may be given with reduced teaching and more self studies.