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Text Segmentation Model Based LDA and Ontology for Question Answering in Agriculture

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Proceedings of 2013 World Agricultural Outlook Conference

Abstract

Question answering system based on text collections has been one research focus in information technology. The significant problem for text collections was how to construct models for text and segmentations. An approach to building topic models based on a formal generative model of documents, Latent Dirichlet Allocation (LDA), is heavily cited in the machine learning literature, but its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use LDA to improve answer retrieval. We propose an LDA-based segmentation model within the language modelling framework, and evaluate it on text segmentation collections for agriculture cultivation. Gibbs sampling is employed to conduct approximate inference in LDA and the computational complexity is analyzed. The process of generating answers in agriculture cultivation question answering system (ACQA_onto) was presented. We demonstrate LDA’s improved expressiveness over traditional QA system based information retrieval with visualizations of answers accurate.

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Acknowledgements

This paper is the sub item of key Technologies for Agricultural Field Information Comprehensive Sensing and Rural extension (Item No.: 2011BAD21B01) of National Science and Technology Support Program.

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Authors and Affiliations

  1. Institute of agriculture information, Chinese Academy of Agriculture Sciences, Beijing, 100081, China

    Depeng Hu, Wensheng Wang, Nengfu Xie & GuoWei Yin

  2. Graduate School, Chinese Academy of Agricultural Sciences, Beijing, 100081, China

    Depeng Hu

  3. Information School, Liaocheng Vocational and Technical College, Liaocheng, Shangdong, 252000, People’s Republic of China

    Shuyu Liu

Authors
  1. Depeng Hu
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  2. Wensheng Wang
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  3. Shuyu Liu
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  4. Nengfu Xie
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  5. GuoWei Yin
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Editors and Affiliations

  1. Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

    Shiwei Xu

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Hu, D., Wang, W., Liu, S., Xie, N., Yin, G. (2014). Text Segmentation Model Based LDA and Ontology for Question Answering in Agriculture. In: Xu, S. (eds) Proceedings of 2013 World Agricultural Outlook Conference. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54389-0_27

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  • DOI: https://doi.org/10.1007/978-3-642-54389-0_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54388-3

  • Online ISBN: 978-3-642-54389-0

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