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Identifying useful and important information within retrieved documents

Arora, Piyush orcid logoORCID: 0000-0002-4261-2860 and Jones, Gareth J.F. orcid logoORCID: 0000-0003-2923-8365 (2017) Identifying useful and important information within retrieved documents. In: Conference on Human Information Interaction and Retrieval (CHIIR '17), 7 - 11 Mar 2017, Oslo, Norway. ISBN 978-1-4503-4677-1

Abstract
We describe an initial study into the identification of important and useful information units within documents retrieved by an information retrieval system in response to a user query created in response to an underlying information need. This study is part of a larger investigation of the exploitation of useful and important units from retrieved documents to generate rich document surrogates to improve user search experience. We report three user studies using a crowdsourcing platform, where participants were first asked to read an information need and contents of a relevant document and then to perform actions depending on the type of study: i) write important information units (WIIU), ii) highlight important information units (HIIU) and iii) assess importance of already highlighted information units (AIHIU). Further, we discuss a novel mechanism for measuring similarities between content annotations. We find majority agreement of about 0.489 and pairwise agreement of 0.340 among users annotation in the AIHIU study, and average cosine similarity of 0.50 and 0.57 between participant annotations and documents in the WIIU and HIIU studies respectively.
Metadata
Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Published in: Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval. . ACM. ISBN 978-1-4503-4677-1
Publisher:ACM
Official URL:http://dx.doi.org/10.1145/3020165.3022154
Copyright Information:© 2017 ACM
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 ADAPT Centre at Dublin City University (Grant No: 12/CE/I2267).
ID Code:22804
Deposited On:03 Dec 2018 11:32 by Piyush Arora . Last Modified 31 Jan 2019 12:24
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