LFU:online

Research Area Digital Science Center (DiSC) Research Area Digital Science Center (DiSC)

Ass.-Prof. Mag. Dr. Dr. Joseph Wang-Kathrein Ass.-Prof. Mag. Dr. Dr. Joseph Wang-Kathrein, +43 512 507 45010, +43 512 507 39760

198845

VU Data Analysis II: Information Retrieval and Full-Text Search

VU 3

5

weekly

annually

English

The students should get an overview over Information Retrieval while deepening their knowledge on text processing methods used for full text search engines. They will acquire necessary abilities to create and adjust indexing and searching algorithms.

After a general introduction to Information Retrieval (definition, tasks etc.) students will be confronted with challenges in creating a search engine. They will learn different ways of processing texts (e.g. tokenization, stemming, lemmatization etc.) in order to overcome those challenges and create a functioning program that is able to perform full text search.

Lecture with exercises.

The following factors will influence the final grade: Participation in exercises (60%), and the result of the exams (40%).

Ch. D. Manning, P. Raghavan, H. Schütze: Introduction to Information Retrieval; Online Edition, Cambridge UP 2009 https://nlp.stanford.edu/IR-book/information-retrieval-book.html

Other literature will be announced at the beginning of the course.

In order to finish the course, students will need their own computer on which different tools will be installed. It is imperative that the students know at least one programming language. During the course we will be programming in Python.

Please note that understanding of data-types and data-structures as well as the ability to install and embed software libraries is a prerequisite of the course.

The acceptance is based on prioritised randomisation. Active students of Complementary Subject Area Digital Science get precedence.

see dates