Information extraction is the process of deriving structured information (such as alive(Elvis)) from digital text (such as the sentence "Elvis is alive"). We will focus on factual and semantic information extraction, i.e., we will cover named entity recognition, entity disambiguation, instance extraction, and fact extraction. We will also touch upon applications of both Information Extraction and the Semantic Web, such as Google’s knowledge graph, IBM’s Watson question answering system, and Facebook’s Open Graph, and academic projects such as YAGO, DBpedia, and NELL. Finally, we will talk about how the big Internet companies use the information that they extract and gather, and how we can protect ourselves against these practices.
- Teacher: Lihu Chen
- Teacher: Jonathan Lajus
- Teacher: Fabian Suchanek
Information extraction is the process of deriving structured information (such as alive(Elvis))
from digital text (such as the sentence "Elvis is alive"). We will
focus on factual and semantic information extraction, i.e., we will
cover named entity recognition, entity disambiguation, instance
extraction, and fact extraction. We will also touch upon applications of
both Information Extraction and the Semantic Web, such as Google’s knowledge graph, IBM’s Watson question answering system, and Facebook’s Open Graph, and academic projects such as YAGO, DBpedia, and NELL.
Finally, we will talk about how the big Internet companies use the
information that they extract and gather, and how we can protect
ourselves against these practices.
- Teacher: Jonathan Lajus
- Teacher: Julien Romero
- Teacher: Fabian Suchanek
- Teacher: Jean-Louis Dessalles
- Teacher: Etienne Houzé
- Teacher: Pierre-Alexandre Murena
- Teacher: Flavia Salutari