Ranking health web pages with relevance and understandability
Palotti, Joao, Goeuriot, Lorraine, Zuccon, Guido, & Hanbury, Allan (2016) Ranking health web pages with relevance and understandability. In 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '16), 17-21 July 2016, Pisa, Italy.
We propose a method that integrates relevance and understandability to rank health web documents. We use a learning to rank approach with standard retrieval features to determine topical relevance and additional features based on readability measures and medical lexical aspects to determine understandability. Our experiments measured the effectiveness of the learning to rank approach integrating understandability on a consumer health benchmark. The findings suggest that this approach promotes documents that are at the same time topically relevant and understandable.
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|Item Type:||Conference Paper|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science|
|Copyright Owner:||Copyright 2016 The Author(s)|
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|Deposited On:||15 Sep 2016 22:45|
|Last Modified:||27 Sep 2016 07:49|
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