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- W3146893722 abstract "Abstract 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." @default.
- W3146893722 created "2021-04-13" @default.
- W3146893722 creator A5008757230 @default.
- W3146893722 creator A5010064223 @default.
- W3146893722 creator A5026167460 @default.
- W3146893722 creator A5045249230 @default.
- W3146893722 creator A5052791434 @default.
- W3146893722 creator A5082559201 @default.
- W3146893722 date "2021-04-05" @default.
- W3146893722 modified "2023-10-14" @default.
- W3146893722 title "Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges" @default.
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