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Knowledge Bases

A knowledge base (KB) is a structured, computer-processable description of the world. A KB can be thought of as a graph, in which the nodes are entities and the edges are relations. Here is an example:
A knowledge base is a graph
KBs serve all kinds of purposes, such as natural language understanding in chatbots, intelligent assistance, or Web search. Our research is guided by specific real-world problems on KBs. I work together with my colleagues and students in the DIG Team of Télécom Paris to formalize problems, to design principled models for their solution, and to develop real systems that produce that solution.
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We are launching our project on natural language processing and knowledge bases with 4 industrial partners. We are hiring 4 PhD students and 3 engineers or postdocs.
Apart from that, we work on several projects around knowledge bases:
Logo of YAGO
Knowledge Base Construction
We work on extracting computer-readable information from Web sources. Our flagship project in this domain is YAGO, a large knowledge base constructed from Wikidata, schema.org, and other Web sources. But we also work on extracting commercial products from the Web and on repairing regular expressions.
Completeness mining
In the frame of an ANR grant, our goal is to find automatically where a knowledge base is missing information. Our flagship project here is the AMIE rule mining system, but we also work on determining the completeness of entities, or the necessity of attributes. Here is an overview on our work of mining completeness in knowledge bases.
We have developed several approaches to query knowledge bases efficiently: One approach is based on Bash commands. Another one allows querying the knowledge base through Web services.
Finally, we also work on applications of knowledge bases, such as Combinatorial creativity (making computers creative) or Semantic Culturomics (mining trends in history and society).

Older projects are

Students / PostDocs

Former Students / PostDocs

Further information