Arora, Piyush ORCID: 0000-0002-4261-2860 (2015) Promoting user engagement and learning in amorphous search tasks. In: 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’15), 9 - 13 Aug 2015, Santiago, Chile. ISBN 978-1-4503-3621-5
Abstract
Much research in information retrieval (IR) focuses on optimization of the rank of relevant retrieval results for single shot ad hoc IR tasks. Relatively little research has been carried out on user engagement to support more complex search tasks. We seek to improve user engagement for IR tasks by providing richer representation of retrieved information. It is our expectation that this strategy will promote implicit learning within search activities. Specifically, we plan to explore methods of finding semantic concepts within retrieved documents, with the objective of creating improved document surrogates. Further, we would like to study search effectiveness in terms of different facets such as the user’s search experience, satisfaction, engagement and learning. We intend to investigate this in an experimental study, where our richer document representations are compared
with the traditional document surrogates for the same user queries.
Metadata
Item Type: | Conference or Workshop Item (Other) |
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Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Information Search and Retrieval; Information Interfaces and Presentation; Interaction styles; interactive IR; learning; engagement |
Subjects: | Computer Science > Information retrieval |
DCU Faculties and Centres: | UNSPECIFIED |
Published in: | Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. . ACM. ISBN 978-1-4503-3621-5 |
Publisher: | ACM |
Official URL: | http://dx.doi.org/10.1145/2766462.2767848 |
Copyright Information: | © 2015 The Author |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland (SFI) as a part of the CNGL Centre for Global Intelligent Content at DCU (Grant No: 12/CE/I2267). |
ID Code: | 22798 |
Deposited On: | 30 Nov 2018 14:41 by Piyush Arora . Last Modified 31 Jan 2019 12:20 |
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