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Facilitating access to health web pages with different language complexity levels

Alfano, Marco orcid logoORCID: 0000-0001-7200-9547, Lenzitti, Biagio orcid logoORCID: 0000-0003-2664-7788, Taibi, Davide orcid logoORCID: 0000-0002-0785-6771 and Helfert, Markus orcid logoORCID: 0000-0001-6546-6408 (2019) Facilitating access to health web pages with different language complexity levels. In: International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE) 2019, 2-4 May 2019, Heraklion, Crete, Greece.

Abstract
The number of people looking for health information on the Internet is constantly growing. When searching for health information, different types of users, such as patients, clinicians or medical researchers, have different needs and should easily find the information they are looking for based on their specific requirements. However, generic search engines do not make any distinction among the users and, often, overload them with the provided amount of information. On the other hand, specific search engines mostly work on medical literature and specialized web sites are often not free and contain focused information built by hand. This paper presents a method to facilitate the search of health information on the web so that users can easily and quickly find information based on their specific requirements. In particular, it allows different types of users to find health web pages with required language complexity levels. To this end, we first use the structured data contained in the web to classify health web pages based on different audience types such as, patients, clinicians and medical researchers. Next, we evaluate the language complexity levels of the different web pages. Finally, we propose a mapping between the language complexity levels and the different audience types that allows us to provide different types of users, e.g., experts and non-experts with tailored web pages in terms of language complexity.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:e-Health; Health Information Seeking; User Requirements; Language Complexity; Structured Data on the Web
Subjects:Computer Science > Information retrieval
Computer Science > World Wide Web
Medical Sciences > Health
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > Lero: The Irish Software Engineering Research Centre
Published in: Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE. . SciTePress.
Publisher:SciTePress
Official URL:https://doi.org/10.5220/0007740301130123
Copyright Information:2019 the Authors. (CC BY-NC-ND 4.0)
ID Code:23104
Deposited On:01 May 2019 14:48 by Marco Alfano . Last Modified 01 Mar 2022 15:41
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