Intention mining is a promising research area of data mining that aims to determine end-users’ intentions from their past activities stored in the logs, which note users’ interaction with the system. Search engines are a major source to infer users’ past searching activities to predict their intention, facilitating the vendors and manufacturers to present their products to the user in a promising manner. This area has been consistently getting pertinence with an increasing trend for online purchasing. Noticeable research work has been accomplished in this area for the last two decades. There is no such systematic literature review available that provides a comprehensive review in intension mining domain to the best of our knowledge. This article presents a systematic literature review based on 109 high-quality research papers selected after rigorous screening. The analysis reveals that there exist eight prominent categories of intention. Furthermore, a taxonomy of the approaches and techniques used for intention mining have been discussed in this article. Similarly, six important types of data sets used for this purpose have also been discussed in this work. Lastly, future challenges and research gaps have also been presented for the researchers working in this domain.

意图挖掘是数据挖掘的一个有前途的研究领域，旨在从最终用户存储在日志中的过去活动中确定最终用户的意图，该活动记录了用户与系统的交互。搜索引擎是推断用户过去的搜索活动以预测其意图的主要来源，从而有助于供应商和制造商以有希望的方式向用户展示其产品。随着在线购买趋势的发展，这一领域一直与时俱进。在过去的二十年中，该领域已经完成了引人注目的研究工作。就我们所知，尚无此类系统的文献综述可提供有关强度开采领域的全面综述。本文基于经过严格筛选的109篇高质量研究论文，提供了系统的文献综述。分析表明，存在八个主要的意图类别。此外，本文还讨论了用于意图挖掘的方法和技术的分类法。同样，在此工作中还讨论了用于此目的的六种重要类型的数据集。最后，还为该领域的研究人员提出了未来的挑战和研究差距。在这项工作中，还讨论了用于此目的的六种重要类型的数据集。最后，还为该领域的研究人员提出了未来的挑战和研究差距。在这项工作中，还讨论了用于此目的的六种重要类型的数据集。最后，还为该领域的研究人员提出了未来的挑战和研究差距。