Exposing knowledge: providing a real-time view of the domain under study for students

Zammit, Omar, De Raffaele, Clifford ORCID: https://orcid.org/0000-0002-7081-702X, Smith, Serengul ORCID: https://orcid.org/0000-0003-0777-5637 and Petridis, Miltos ORCID: https://orcid.org/0000-0003-1275-1023 (2019) Exposing knowledge: providing a real-time view of the domain under study for students. Bramer, Max and Petridis, Miltos ORCID: https://orcid.org/0000-0003-1275-1023, eds. Artificial Intelligence XXXVI: 39th SGAI International Conference on Artificial Intelligence (AI-2019), Cambridge, UK, December 17–19, 2019, Proceedings. In: AI-2019 Thirty-ninth SGAI International Conference on Artificial Intelligence, 17-19 Dec 2019, Cambridge, United Kingdom. ISBN 9783030348847, e-ISBN 9783030348854. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-030-34885-4_9)

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Official URL: https://doi.org/10.1007/978-3-030-34885-4_9

Abstract

With the amount of information that exists online, it is impossible for a student to find relevant information or stay focused on the domain under study. Research showed that search engines have deficiencies that might prevent students from finding relevant information. To this end, this research proposes a technical solution that takes the personal search history of a student into consideration and provides a holistic view of the domain under study. Based on algorithmic approaches to assert semantic similarity, the proposed framework makes use of a user interface to dynamically assist students through aggregated results and wordcloud visualizations. The effectiveness of our approach is finally evaluated through the use of commonly used datasets and compared in line with existing research.

Item Type:	Conference or Workshop Item (Paper)
Research Areas:	A. > School of Science and Technology > Computer Science
Item ID:	27617
Notes on copyright:	This is a post-peer-review, pre-copyedit version of an article published in rtificial Intelligence XXXVI. SGAI 2019. Lecture Notes in Computer Science, vol 11927. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-34885-4_9
Useful Links:	Event Middlesex University Expert Profile Middlesex University Expert Profile Publication Publisher Publisher's T&Cs Publisher's T&Cs
Depositing User:	Serengul Smith
Date Deposited:	23 Sep 2019 21:39
Last Modified:	29 Nov 2022 18:41
URI:	https://eprints.mdx.ac.uk/id/eprint/27617

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