[ 921CGELWSMK13 ] KV Web Search and Mining

Es ist eine neuere Version 2022W dieser LV im Curriculum Master's programme Computer Science 2023W vorhanden.
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M2 - Master's programme 2. year Computer Science Birgit Pröll 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2013W
Objectives Students have competence in fundamentals and technologies of (1) web search (web information retrieval) and their application in search engines, as well as in (2) web mining with an emphasis on web information extraction. They are able to implement and evaluate applications in these fields and have knowledge about related fields and current research topics.
Subject Information retrieval „in a nutshell“; web search, search engines, web crawling, weighting and ranking (PageRank etc.), search user interfaces (advances query concepts etc.), web search evaluation, site search; search engine optimization (SEO)

Information extraction „in a nutshell“; Web information extraction (WebIE) funcamentals, WebIE approaches (knowledge-based Web IE, wrapper generation etc.), web link/structure analysis, WebIE tools and aplications

Specific concepts and applications: deep web search, spam detection, question answering systems, social search, social media search and analysis, opinion mining /sentiment analysis, crowd knowledge extraction, WebIE-based ontology learning, web data quality, etc.

Criteria for evaluation exercises (45%), exam (45%), in-class contribution (10%)
Methods presentation, exercises
Language English
Study material Search Engines (B. Croft; Pearson 2010)
Changing subject? No
Corresponding lecture (*)INMAWKVWEIR: KV Web Information Retrieval (3 ECTS) bzw. 921INFWWIRK12: KV Web Information Retrieval and Extraction (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment