Lehre/Vorlesung Information Service Engineering
Aus Aifbportal
Vorlesung Information Service Engineering
Details zur Lehrveranstaltung
| Dozent(en) | Harald Sack |
| Übungsleiter | Mahsa Vafaie, Mary-Ann Tan, Ebrahim Norouzi, Cristian Santini |
| Fach (Gebiet) | Informatik |
| Leistungspunkte | 5 ECTS |
| Erfolgskontrolle | Klausur |
| Semester |
Aktuelle und ergänzende Informationen, sowie Zeiten und Räume der Lehrveranstaltung finden Sie im Vorlesungsverzeichnis der Universität.
Link zum Vorlesungsverzeichnis
Link zum Studierendenportal
Forschungsgruppe
Inhalt
In this lecture, the students will learn the fundamentals of natural language processing, knowledge graphs, and basic machine learning as required for the development of information services.
Literatur
- D. Jurafsky, J.H. Martin, Speech and Language Processing, 2nd ed. Pearson Int., 2009.
- A. Hogan, The Web of Data, Springer, 2020.
- G. Rebala, A. Ravi, S. Churiwala, An Introduction to Machine Learning, Springer, 2019.
Content:
- Data, Information, Knowledge and Wisdom
- Natural Language Processing
- Knowledge Graphs
- Basic Machine Learning
- ISE Applications
Learning objectives:
- The students know the fundamentals and measures of information theory and are able to apply those in the context of Information Service Engineering.
- The students have basic skills of natural language processing and are enabled to apply natural language processing technology to solve and evaluate simple text analysis tasks.
- The students have fundamental skills of knowledge representation with ontologies as well as basic knowledge of Semantic Web and Linked Data technologies. The students are able to apply these skills for simple representation and analysis tasks.
- The students have fundamental skills of information retrieval and are enabled to conduct and to evaluate simple information retrieval tasks.
- The students apply their skills of natural language processing, Linked Data engineering, and Information Retrieval to conduct and evaluate simple knowledge mining tasks.
- The students know the fundamentals of recommender systems as well as of semantic and exploratory search.