Explicit diversification of search results across multiple dimensions for educational search

Yigit-Sert, S., Altingovde, I. S., Macdonald, C. , Ounis, I. and Ulusoy, Ö. (2021) Explicit diversification of search results across multiple dimensions for educational search. Journal of the Association for Information Science and Technology, 72(3), pp. 315-330. (doi: 10.1002/asi.24403)

Abstract

Making use of search systems to foster learning is an emerging research trend known as search as learning. Earlier works identified result diversification as a useful technique to support learning‐oriented search, since diversification ensures a comprehensive coverage of various aspects of the queried topic in the result list. Inspired by this finding, first we define a new research problem, multidimensional result diversification, in the context of educational search. We argue that in a search engine for the education domain, it is necessary to diversify results across multiple dimensions, that is, not only for the topical aspects covered by the retrieved documents, but also for other dimensions, such as the type of the document (e.g., text, video, etc.) or its intellectual level (say, for beginners/experts). Second, we propose a framework that extends the probabilistic and supervised diversification methods to take into account the coverage of such multiple dimensions. We demonstrate its effectiveness upon a newly developed test collection based on a real‐life educational search engine. Thorough experiments based on gathered relevance annotations reveal that the proposed framework outperforms the baseline by up to 2.4%. An alternative evaluation utilizing user clicks also yields improvements of up to 2% w.r.t. various metrics.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Macdonald, Professor Craig and Ounis, Professor Iadh
• Authors: Yigit-Sert, S., Altingovde, I. S., Macdonald, C., Ounis, I., and Ulusoy, Ö.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Journal of the Association for Information Science and Technology
• Publisher: Wiley
• ISSN: 2330-1635
• ISSN (Online): 2330-1643
• Published Online: 12 September 2020
• Copyright Holders: Copyright © 2020 Association for Information Science and Technology
• First Published: First published in Journal of the Association for Information Science and Technology 72(3):315-330
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
171404		Newton International Fellowship Exchange	Craig MacDonald	The Royal Society (ROYSOC)	NI140231	Computing Science