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On Automatic Question Answering Using Efficient Primal-Dual Models

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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction (MPRSS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10183))

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Abstract

Automatic question answering has been a major problem in natural language processing since the early days of research in the field. Given a large dataset of question-answer pairs, the problem can be tackled using text matching in two steps: find a set of similar questions to a given query from the dataset and then provide an answer to the query by evaluating the answers stored in the dataset for those questions. In this paper, we treat the text matching problem as an instance of the inexact graph matching problem and propose an efficient approximate matching scheme. We utilize the well known quadratic optimization problem metric labeling as the framework of graph matching. In order to solve the text matching, we first embed the sentences given in natural language into a weighted directed graph. Next, we present a primal-dual approximation algorithm for the linear programming relaxation of the metric labeling problem to match text graphs. We demonstrate the utility of our approach on a question answering task over a large dataset which involves matching of questions as well as plain text.

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Author information

Authors and Affiliations

  1. Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, USA

    Yusuf Osmanlıoğlu

  2. Department of Computer Science, Drexel University, Philadelphia, USA

    Ali Shokoufandeh

Authors
  1. Yusuf Osmanlıoğlu
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  2. Ali Shokoufandeh
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Correspondence to Yusuf Osmanlıoğlu .

Editor information

Editors and Affiliations

  1. Universität Ulm, Ulm, Germany

    Friedhelm Schwenker

  2. Multimodal Communication and Computation, University of Southern California, Playa Vista, California, USA

    Stefan Scherer

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Osmanlıoğlu, Y., Shokoufandeh, A. (2017). On Automatic Question Answering Using Efficient Primal-Dual Models. In: Schwenker, F., Scherer, S. (eds) Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction. MPRSS 2016. Lecture Notes in Computer Science(), vol 10183. Springer, Cham. https://doi.org/10.1007/978-3-319-59259-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-59259-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59258-9

  • Online ISBN: 978-3-319-59259-6

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