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A survey on intention analysis: successful approaches and open challenges

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Abstract

Intention Analysis is a computational task that analyzes people’s desires, wishes, and attitudes from user-generated texts. This sub-field of text mining has recently attracted research interest. This research paper provides an overview and an analysis of the latest studies in this field. These studies were categorized and summarized according to their contributions and the techniques they used. Several proposed approaches and some real applications were investigated in depth and presented in detail. Moreover, some related fields to intention analysis such as Transfer Learning (TL), Spam Detection (SD), and Building Resources (BR) were discussed in this survey of the literature dedicated to Intention Analysis. The aim of this survey is to give a comprehensive view of the intention analysis field supported by a number of graphics and summary tables about the literature. The paper concludes by identifying a number of research topics that can be promising for future research.

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Notes

  1. https://www.webtretho.com/

  2. http://www.svmlight.joachims.org

  3. https://hadoop.apache.org/

  4. https://www.paralleldots.com/

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Authors and Affiliations

  1. Department of Computer Science, ISG-Tunis, University of Tunis, Tunis, Tunisia

    Mohamed Hamroun & Mohamed Salah Gouider

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  1. Mohamed Hamroun
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  2. Mohamed Salah Gouider
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Correspondence to Mohamed Hamroun.

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Hamroun, M., Gouider, M.S. A survey on intention analysis: successful approaches and open challenges. J Intell Inf Syst 55, 423–443 (2020). https://doi.org/10.1007/s10844-020-00604-x

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