6533b829fe1ef96bd128a5a0
RESEARCH PRODUCT
Language complexity in on-line health information retrieval
Biagio LenzittiMarkus HelfertDavide TaibiMarco Alfanosubject
020205 medical informaticsComputer scienceKnowledge management02 engineering and technologyUser requirements document01 natural sciencesSearch engineSeekersPatient empowerment; E-Health Health Information Seeking; User Requirements; Language Complexity; Structured Data on the Web0202 electrical engineering electronic engineering information engineeringInformation retrievalComputer softwareSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalLanguage complexitySettore INF/01 - InformaticaLanguage complexityPoint (typography)Consumer behaviourCommunicationSpecific-information010401 analytical chemistry0104 chemical sciencesHealthOrder (business)Health information seekingUser requirementsE-HealthStructured data on the webMedical literaturedescription
The number of people searching for on-line health information has been steadily growing over the years so it is crucial to understand their specific requirements in order to help them finding easily and quickly the specific in-formation they are looking for. Although generic search engines are typically used by health information seekers as the starting point for searching information, they have been shown to be limited and unsatisfactory because they make generic searches, often overloading the user with the provided amount of results. Moreover, they are not able to provide specific information to different types of users. At the same time, specific search engines mostly work on medical literature and provide extracts from medical journals that are mainly useful for medical researchers and experts but not for non-experts. A question then arises: Is it possible to facilitate the search of on-line health/medical information based on specific user requirements? In this pa-per, after analysing the main characteristics and requirements of on-line health seeking, we provide a first answer to this question by exploiting the Web structured data for the health domain and presenting a system that allows different types of users, i.e., non-medical experts and medical experts, to retrieve Web pages with language complexity levels suitable to their expertise. Furthermore, we apply our methodology to the results of a generic search engine, such as Google, in order to re-rank them and provide different users with the proper health/medical Web pages in terms of language complexity.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-07-08 |