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Sparse Single-Hidden Layer Feedforward Network for Mapping Natural Language Questions to SQL Queries

  • Issam H. Laradji
  • Lahouari Ghouti
  • Faisal Saleh
  • Musab A. AlTurki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)

Abstract

Mapping natural language (NL) statements into SQL queries allows users to interact with systems through everyday language. Semantic parsing has seen a growing interest over the past decades. In this paper, we extend single hidden layer feedforward network (SLFN) by adding the Kullback-Liebler (KL) divergence parameter to its objective function. We refer to this algorithm as Sparse SLFN (S-SLFN) which can learn whether an SQL query answers a particular NL question. With Bag of Words (BoW) representing the questions and the queries, the algorithm, by enforcing sparsity, is meant to retain robust features representing informative relationships and structure of the data. Experimental results show that S-SLFN outperforms SLFN and other algorithms for the GeoQueries dataset by a respectable margin.

Keywords

Single-hidden Layer Feedforward Network (SLFN) Sparsity Semantic Parsing 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Issam H. Laradji
    • 1
  • Lahouari Ghouti
    • 1
  • Faisal Saleh
    • 1
  • Musab A. AlTurki
    • 1
  1. 1.Department of Information and Computer ScienceKing Fahd University of Petroleum and MineralsDhahranSaudi Arabia

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