The goals of this course are the following:

• Gain a fundamental understanding about how (web) search engines (like Google, Bing, Lucene, Elasticsearch, …) work
• Learn how to efficiently search a large number of documents and rank them according to their relevance to a given query
• Learn how to evaluate search results and incorporate additional context information (like PageRank) to improve search results
• Additionally, learn how to compare and search for audio and images

• Text indexing, Stemming, Tokenization, Inverted Index, BOW
• Audio indexing: MFCCs, Rhythmpatterns, Statistical Spectrum Descriptors
• Image Indexing:  Color histograms, Edge histograms, Texture
• Cross-modal Aspects: Image characteristics of text, Text in audio and images,...
• Boolean Retrieval, Vector Space Model, Binary-Independence-Retrieval-Modell, Statistical language models
• Evaluation

ECTS/Effort:

Lectures: 7 sessions @ 2h: 14h

Exercises:

     Ex1: 30h

     EX2: 10h

Exam Preparation: 20h

Exam: 1h

SUM: 75h

Lectures:

11.10 Introduction
18.10 Basic text Processing
25.10 Information on Exercise 1
8.11 Scoring and Search
22.11 IR Evaluation
29.11 Web search
13.12 Search Interfaces
20.12 Image and Music IR

Exercise 1:

25.10 Hand-out
23.11 Programming Café
13.12 Hand-in in TISS
14.12 Hand-in Discussion

Exercise 2:

20.12 Hand-out
25.1 Hand-in in TUWEL