6533b7ddfe1ef96bd1273db9
RESEARCH PRODUCT
Facilitating Access to Health Web Pages with Different Language Complexity Levels
Markus HelfertMarco AlfanoBiagio LenzittiDavide Taibisubject
Health Information Seeking020205 medical informaticsComputer science02 engineering and technologyUser requirements documentUser RequirementsWorld Wide Web03 medical and health sciencesSearch engine0302 clinical medicineStructured Data on the WebWeb page0202 electrical engineering electronic engineering information engineeringInformation retrievale-Health; Health Information Seeking; User Requirements; Language Complexity; Structured Data on the Web030212 general & internal medicineLanguage complexitySettore INF/01 - Informaticabusiness.industryWorld Wide WebLanguage ComplexityWork (electrical)HealthThe InternetE-HealthHealth informationbusinessMedical literaturedescription
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.
year | journal | country | edition | language |
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2019-05-02 |