392272 ISY Project: Information Extraction from Web Tables (Pj) (SoSe 2017)

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- Short Description

The Web contains a large number (billions) of tables (e.g., HTML tables, spreadsheet documents). Many of these tables contain structured information that could be extracted and added to a knowledge base. Given such a knowledge base, important tasks such as search and question answering can be supported. To do so, the content of a table needs to be understood and represented in terms of an ontology.

Given a set of tables extracted from the Web and a large knowledge base (DBpedia), the task of the project is i) to align entries from tables to entries in the knowledge base, ii) to build hypotheses about what a table expresses (in the form of an RDF graph pattern), iii) to find the best hypothesis, and finally, iv) to populate a knowledge base given the information extracted from the tables.

An influential paper on table understanding is "Understanding tables
on the web" (2012) by Microsoft Research Asia: Jingjing Wang, Bin Shao, Haixun Wang, Kenny Q. Zhu.

- Required skills (e.g. mandatory courses, if required)

  • programming skills are required (e.g., Perl, Python, Java, ...). However, in a group of several students, conceptual and implementational work can be distributed among the group members.
  • knowledge of Semantic Web technologies (RDF, SPARQL) is a plus, but can be obtained during the project

Please note that the teams will be selected by the supervisors on the basis of short applications that students are expected to send to them. Registering to the project in the ekVV will only be regarded as expression of interest; it will not secure a team membership.
Please get in touch with the supervisors for information on the application procedure.

Teaching staff

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Subject assignments

Module Course Requirements  
39-M-Inf-GP Grundlagenprojekt Intelligente Systeme Gruppenprojekt Ungraded examination
Student information

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Registered number: 7
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Address:
SS2017_392272@ekvv.uni-bielefeld.de
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2 Students to be reached directly via email
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Last update basic details/teaching staff:
Friday, January 27, 2017 
Last update times:
Friday, January 27, 2017 
Last update rooms:
Friday, January 27, 2017 
Type(s) / SWS (hours per week per semester)
project (Pj) / 4
Department
Faculty of Technology
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ID
92380254