| Detailinformationen |
| Quellcurriculum |
Masterstudium Computer Science 2021S |
| Ziele |
(*)Students have competence in fundamentals and technologies of (1) Web Search and their application in search engines (2) Web Mining including web scraping and social media mining and (3) Question Answering and Chatbots. They are able to implement and evaluate applications in these fields and have knowledge about related fields and current research topics
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| Lehrinhalte |
(*)1) Web Search
- information retrieval „in a nutshell“
- web search challenges
- search engines: Google, Quant et al.
- web crawling
- weighting and ranking: PageRank etc.
- search engines evaluation
- site search
- search engine optimization (SEO)
- search engine user interfaces
- social media search
- deep web search
- spam and defacement detection
- tools and applications
2) Web Mining
- information extraction „in a nutshell“
- web information extraction challenges
- web scraping
- crowd/knowledge-based extraction
- social media mining (twitter, blogs etc.), opinion mining, sentiment analysis
- tools and applications
3) Question Answering & Chatbots
- approaches and architectures
- tools and applications
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| Beurteilungskriterien |
(*)exercises, exam, in-class contribution
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| Lehrmethoden |
(*)slide presentation (slides on Moodle), exercises (group work)
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)- Croft, Donald Metzler, Trevor Strohman: Search Engines – Information Retrieval in Practice, Pearson 2010
- Daniel Jurafsky, James H. Martin: Speech and Language Processing: An Introduction to Natural Language Processing, Prentice Hall 2000
- Marti A. Hearst: Search User Interfaces, Cambridge University Press 2009
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| Lehrinhalte wechselnd? |
Nein |
| Äquivalenzen |
INMAWKVWEIR: KV Web Information Retrieval (3 ECTS) bzw. 921INFWWIRK12: KV Web Information Retrieval and Extraction (3 ECTS)
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