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Statistical Relational Data Integration for Information Extraction

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Reasoning Web. Semantic Technologies for Intelligent Data Access (Reasoning Web 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8067))

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Abstract

These lecture notes provide a brief overview of some state of the art large scale information extraction projects. Consequently, these projects are related to current research activities in the semantic web community. The majority of the learning algorithms developed for these information extraction projects are based on the lexical and syntactical processing of Wikipedia and large web corpora. Due to the size of the processed data and the resulting intractability of the associated inference problems existing knowledge representation formalism are often inadequate for the task. We will present recent advances in combining tractable logical and probabilistic models that bring statistical language processing and rule-based approaches closer together. With these lecture notes we hope to convince the attendees that there are numerous synergies and research agendas that can arise when uncertainty-based data-driven research meets rule-based schema-driven research. We also describe certain theoretical and practical advances in making probabilistic inference scale to very large problems.

These lecture notes are based on several previous publications of the author and his colleagues in conference proceedings such as AAAI, UAI, IJCAI, and ESWC.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA

    Mathias Niepert

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  1. Mathias Niepert
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  1. Fakultät Informatik, Technische Universität Dresden, Nöthnitzer Str. 46, 01062, Dresden, Germany

    Sebastian Rudolph

  2. Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, OX1 3 QD, Oxford, UK

    Georg Gottlob  & Ian Horrocks  & 

  3. Department of Computer Science, Vrije Universiteit Amsterdam, de Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands

    Frank van Harmelen

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Niepert, M. (2013). Statistical Relational Data Integration for Information Extraction. In: Rudolph, S., Gottlob, G., Horrocks, I., van Harmelen, F. (eds) Reasoning Web. Semantic Technologies for Intelligent Data Access. Reasoning Web 2013. Lecture Notes in Computer Science, vol 8067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39784-4_7

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