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Hierarchical Organization of Collaboratively Constructed Content

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The People’s Web Meets NLP

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Abstract

Huge collections of collaboratively constructed content (e.g. blogs, consumer reviews, etc.) are now available online. This content has become a valuable knowledge repository, which enables users to seek quality information. However, such content is often unorganized, leading to difficulty in information navigation and knowledge acquisition. This chapter focuses on discovering the structure of the content and organizing them accordingly, so as to facilitate users in understanding the knowledge inherent within the content. In particular, we employ one example of the collaboratively constructed content, i.e. consumer reviews on products, as a case study, and propose a domain-assisted approach to generate a hierarchical structure to organize the reviews. The hierarchy organizes product aspects as nodes following their parent-child relations. For each aspect, the reviews and corresponding opinions on this aspect are stored. Such hierarchy provides a well-visualized way to browse consumer reviews at different granularity to meet various users’ needs, which can help to improve information dissemination and accessibility. We further apply the generated hierarchy to support the application of opinion Question Answering (opinion-QA) for products, which aims to generate appropriate answers for opinion questions about products. The experimental results on 11 popular products in 4 domains demonstrate the effectiveness of our approach.

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Notes

  1. 1.

    http://www.comp.nus.edu.sg/~Jianxing/Products_Reviews.rar

  2. 2.

    http://nlp.stanford.edu/software/lex-parser.shtml

  3. 3.

    http://thesaurus.com

  4. 4.

    http://cemantix.org/assert.html

  5. 5.

    Available in http://www.aclweb.org/supplementals/D/D11/D11-1013.Attachment.zip

  6. 6.

    Available in http://www.comp.nus.edu.sg/~Jianxing/Product_Reviews.rar

  7. 7.

    Available in http://www.aclweb.org/supplementals/D/D11/D11-1013.Attachment.zip

  8. 8.

    http://nlp.stanford.edu/software/CRF-NER.shtml

  9. 9.

    http://answers.yahoo.com

  10. 10.

    http://www.comp.nus.edu.sg/~Jianxing/auxiliary_material.zip

  11. 11.

    Using stanford POS tagger, http://nlp.stanford.edu/software/tagger.shtml

  12. 12.

    http://svmlight.joachims.org/svm_multiclass.html

  13. 13.

    http://www.comp.nus.edu.sg/~Jianxing/auxiliary_material.zip

  14. 14.

    Empirically set to 10 in the experiment.

  15. 15.

    http://www.comp.nus.edu.sg/~Jianxing/auxiliary_material.zip

  16. 16.

    It represents any pair of words in their sentence order, allowing at most two gaps in between.

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Acknowledgements

This work is supported by NUS-Tsinghua Extreme Search (NExT) project under the grant number: R-252-300-001-490. We give warm thanks to the project and anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. School of Computing, National University of Singapore, AS6, 13 Computing Drive, Singapore, 117417, Singapore

    Jianxing Yu, Zheng-Jun Zha & Tat-Seng Chua

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  1. Jianxing Yu
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  3. Tat-Seng Chua
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Correspondence to Jianxing Yu .

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  1. Department of Computer Science Ubiquitous Knowledge Processing (UKP) Lab, Technische Universität Darmstadt, Darmstadt, Germany

    Iryna Gurevych  & Jungi Kim  & 

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Yu, J., Zha, ZJ., Chua, TS. (2013). Hierarchical Organization of Collaboratively Constructed Content. In: Gurevych, I., Kim, J. (eds) The People’s Web Meets NLP. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35085-6_8

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  • DOI: https://doi.org/10.1007/978-3-642-35085-6_8

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