Knowledge Base Construction
In this class, we will take an overview of Information Extraction techniques and the Semantic Web. Information extraction is the process of deriving structured information (such as alive(Elvis)) from digital text (such as the sentence “Elvis is alive”). The lecture will focus on factual and semantic information extraction, i.e., we will cover named entity recognition, entity disambiguation, instance extraction, fact extraction, and ontological information extraction. We will also touch upon applications of both Information Extraction and the Semantic Web, such as Google's knowledge graph/vault, and IBM's Watson question answering system, as well as academic projects such as YAGO, DBpedia, and NELL.
Course title: Information Extraction
Location: Télécom ParisTech, 46 rue Barrault, 75013 Paris, France
Room: variable, please see the calendar
Time: Every Friday of the second period, starting on 2015-11-27
- Session 1: 13:30-15:00
- Session 2: 15:15 - 16:45
The class will be evaluated by work in the labs and by the final exam. The labs will be a combination of practical work (programming) and exam-like exercises. Every student works on their own. The lab work is to be handed at the beginning of the next lecture.
The final grades are now available here.
Students who did not pass: please contact the lecturer for a re-exam.
The schedule beyond the current point of time is tentative. The PDF slides are provided for convenience only, the authoritative ones are the SVG slides.